@article{zbijewski2015quantitative,

title = {Quantitative Assessment Of Bone And Joint Health On A Dedicated Extremities Cone-Beam CT System.},

author = {Wojciech Zbijewski and Qian Cao and Steven Tilley and Alejandro Sisniega and J. Webster Stayman and John Yorkston and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4451217},

issn = {1861-6429},

year  = {2015},

date = {2015-06-01},

journal = {International journal of computer assisted radiology and surgery},

volume = {10},

number = {Suppl 1},

pages = {S29--S31},

publisher = {NIH Public Access},

keywords = {CBCT, Extremities, Spectral X-ray/CT},

pubstate = {published},

tppubtype = {article}

}

@article{wang2014nesterov,

title = {Accelerated statistical reconstruction for C-arm cone-beam CT using Nesterov's method.},

author = {Adam S. Wang and J. Webster Stayman and Yoshito Otake and Sebastian Vogt and Gerhard Kleinszig and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4425726},

doi = {10.1118/1.4914378},

issn = {0094-2405},

year  = {2015},

date = {2015-05-01},

journal = {Medical physics},

volume = {42},

number = {5},

pages = {2699--708},

abstract = {PURPOSE To accelerate model-based iterative reconstruction (IR) methods for C-arm cone-beam CT (CBCT), thereby combining the benefits of improved image quality and/or reduced radiation dose with reconstruction times on the order of minutes rather than hours. METHODS The ordered-subsets, separable quadratic surrogates (OS-SQS) algorithm for solving the penalized-likelihood (PL) objective was modified to include Nesterov's method, which utilizes "momentum" from image updates of previous iterations to better inform the current iteration and provide significantly faster convergence. Reconstruction performance of an anthropomorphic head phantom was assessed on a benchtop CBCT system, followed by CBCT on a mobile C-arm, which provided typical levels of incomplete data, including lateral truncation. Additionally, a cadaveric torso that presented realistic soft-tissue and bony anatomy was imaged on the C-arm, and different projectors were assessed for reconstruction speed. RESULTS Nesterov's method provided equivalent image quality to OS-SQS while reducing the reconstruction time by an order of magnitude (10.0 ×) by reducing the number of iterations required for convergence. The faster projectors were shown to produce similar levels of convergence as more accurate projectors and reduced the reconstruction time by another 5.3 ×. Despite the slower convergence of IR with truncated C-arm CBCT, comparison of PL reconstruction methods implemented on graphics processing units showed that reconstruction time was reduced from 106 min for the conventional OS-SQS method to as little as 2.0 min with Nesterov's method for a volumetric reconstruction of the head. In body imaging, reconstruction of the larger cadaveric torso was reduced from 159 min down to 3.3 min with Nesterov's method. CONCLUSIONS The acceleration achieved through Nesterov's method combined with ordered subsets reduced IR times down to a few minutes. This improved compatibility with clinical workflow better enables broader adoption of IR in CBCT-guided procedures, with corresponding benefits in overcoming conventional limits of image quality at lower dose.},

keywords = {CBCT, Fast Algorithms, MBIR},

pubstate = {published},

tppubtype = {article}

}

@article{wang2015accelerated,

title = {Accelerated statistical reconstruction for C-arm cone-beam CT using Nesterov's method.},

author = {Adam S. Wang and J. Webster Stayman and Yoshito Otake and Sebastian Vogt and Gerhard Kleinszig and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4425726},

doi = {10.1118/1.4914378},

issn = {0094-2405},

year  = {2015},

date = {2015-05-01},

journal = {Medical physics},

volume = {42},

number = {5},

pages = {2699--708},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE To accelerate model-based iterative reconstruction (IR) methods for C-arm cone-beam CT (CBCT), thereby combining the benefits of improved image quality and/or reduced radiation dose with reconstruction times on the order of minutes rather than hours. METHODS The ordered-subsets, separable quadratic surrogates (OS-SQS) algorithm for solving the penalized-likelihood (PL) objective was modified to include Nesterov's method, which utilizes "momentum" from image updates of previous iterations to better inform the current iteration and provide significantly faster convergence. Reconstruction performance of an anthropomorphic head phantom was assessed on a benchtop CBCT system, followed by CBCT on a mobile C-arm, which provided typical levels of incomplete data, including lateral truncation. Additionally, a cadaveric torso that presented realistic soft-tissue and bony anatomy was imaged on the C-arm, and different projectors were assessed for reconstruction speed. RESULTS Nesterov's method provided equivalent image quality to OS-SQS while reducing the reconstruction time by an order of magnitude (10.0 ×) by reducing the number of iterations required for convergence. The faster projectors were shown to produce similar levels of convergence as more accurate projectors and reduced the reconstruction time by another 5.3 ×. Despite the slower convergence of IR with truncated C-arm CBCT, comparison of PL reconstruction methods implemented on graphics processing units showed that reconstruction time was reduced from 106 min for the conventional OS-SQS method to as little as 2.0 min with Nesterov's method for a volumetric reconstruction of the head. In body imaging, reconstruction of the larger cadaveric torso was reduced from 159 min down to 3.3 min with Nesterov's method. CONCLUSIONS The acceleration achieved through Nesterov's method combined with ordered subsets reduced IR times down to a few minutes. This improved compatibility with clinical workflow better enables broader adoption of IR in CBCT-guided procedures, with corresponding benefits in overcoming conventional limits of image quality at lower dose.},

keywords = {CBCT, Fast Algorithms, MBIR},

pubstate = {published},

tppubtype = {article}

}

@article{gang2015taskb,

title = {Task-driven image acquisition and reconstruction in cone-beam CT.},

author = {Grace Gang and J. Webster Stayman and Tina Ehtiati and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4539970},

doi = {10.1088/0031-9155/60/8/3129},

issn = {1361-6560},

year  = {2015},

date = {2015-04-01},

journal = {Physics in medicine and biology},

volume = {60},

number = {8},

pages = {3129--50},

publisher = {IOP Publishing},

abstract = {This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters in the presence of a realistic anatomical model. Task-based detectability index (d') is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ± 30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e. the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d' for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d' by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the tilt angle that reduced quantum noise in the region of the stimulus by avoiding highly attenuating anatomical structures. The task-driven imaging framework offers a potentially valuable paradigm for prospective definition of acquisition and reconstruction protocols that improve task performance without increase in dose.},

keywords = {CBCT, Customized Acquisition, MBIR, Regularization Design, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{Sisniega2015,

title = {High-fidelity artifact correction for cone-beam CT imaging of the brain.},

author = {Alejandro Sisniega and Wojciech Zbijewski and Jennifer Xu and Hao Dang and J. Webster Stayman and John Yorkston and Nafi Aygun and Vassilis Koliatsos and Jeffrey H. Siewerdsen },

url = {http://www.ncbi.nlm.nih.gov/pubmed/25611041},

doi = {10.1088/0031-9155/60/4/1415},

issn = {1361-6560},

year  = {2015},

date = {2015-02-01},

journal = {Physics in medicine and biology},

volume = {60},

number = {4},

pages = {1415--39},

abstract = {CT is the frontline imaging modality for diagnosis of acute traumatic brain injury (TBI), involving the detection of fresh blood in the brain (contrast of 30-50 HU, detail size down to 1 mm) in a non-contrast-enhanced exam. A dedicated point-of-care imaging system based on cone-beam CT (CBCT) could benefit early detection of TBI and improve direction to appropriate therapy. However, flat-panel detector (FPD) CBCT is challenged by artifacts that degrade contrast resolution and limit application in soft-tissue imaging. We present and evaluate a fairly comprehensive framework for artifact correction to enable soft-tissue brain imaging with FPD CBCT. The framework includes a fast Monte Carlo (MC)-based scatter estimation method complemented by corrections for detector lag, veiling glare, and beam hardening.The fast MC scatter estimation combines GPU acceleration, variance reduction, and simulation with a low number of photon histories and reduced number of projection angles (sparse MC) augmented by kernel de-noising to yield a runtime of ~4 min per scan. Scatter correction is combined with two-pass beam hardening correction. Detector lag correction is based on temporal deconvolution of the measured lag response function. The effects of detector veiling glare are reduced by deconvolution of the glare response function representing the long range tails of the detector point-spread function. The performance of the correction framework is quantified in experiments using a realistic head phantom on a testbench for FPD CBCT.Uncorrected reconstructions were non-diagnostic for soft-tissue imaging tasks in the brain. After processing with the artifact correction framework, image uniformity was substantially improved, and artifacts were reduced to a level that enabled visualization of ~3 mm simulated bleeds throughout the brain. Non-uniformity (cupping) was reduced by a factor of 5, and contrast of simulated bleeds was improved from ~7 to 49.7 HU, in good agreement with the nominal blood contrast of 50 HU. Although noise was amplified by the corrections, the contrast-to-noise ratio (CNR) of simulated bleeds was improved by nearly a factor of 3.5 (CNR = 0.54 without corrections and 1.91 after correction). The resulting image quality motivates further development and translation of the FPD-CBCT system for imaging of acute TBI.},

keywords = {Artifact Correction, Beam Hardening, CBCT, Head/Neck, Scatter Estimation},

pubstate = {published},

tppubtype = {article}

}

@article{Stayman2015,

title = {Task-Based Optimization of Source-Detector Orbits in Interventional Cone-beam CT},

author = {J. Webster Stayman and Grace Gang and Jeffrey H. Siewerdsen },

url = {https://aiai.jhu.edu/papers/Fully3D2015_stayman.pdf},

year  = {2015},

date = {2015-01-01},

journal = {International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},

volume = {13},

keywords = {CBCT, Customized Acquisition, MBIR, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{xu2014cascadedb,

title = {Cascaded systems analysis of photon counting detectors.},

author = {Jennifer Xu and Wojciech Zbijewski and Grace Gang and J. Webster Stayman and Katsuyuki Taguchi and Mats Lundqvist and Erik Fredenberg and John A. Carrino and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4281040},

doi = {10.1118/1.4894733},

issn = {0094-2405},

year  = {2014},

date = {2014-10-01},

urldate = {2014-10-01},

journal = {Medical physics},

volume = {41},

number = {10},

pages = {101907},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE Photon counting detectors (PCDs) are an emerging technology with applications in spectral and low-dose radiographic and tomographic imaging. This paper develops an analytical model of PCD imaging performance, including the system gain, modulation transfer function (MTF), noise-power spectrum (NPS), and detective quantum efficiency (DQE). METHODS A cascaded systems analysis model describing the propagation of quanta through the imaging chain was developed. The model was validated in comparison to the physical performance of a silicon-strip PCD implemented on an experimental imaging bench. The signal response, MTF, and NPS were measured and compared to theory as a function of exposure conditions (70 kVp, 1-7 mA), detector threshold, and readout mode (i.e., the option for coincidence detection). The model sheds new light on the dependence of spatial resolution, charge sharing, and additive noise effects on threshold selection and was used to investigate the factors governing PCD performance, including the fundamental advantages and limitations of PCDs in comparison to energy-integrating detectors (EIDs) in the linear regime for which pulse pileup can be ignored. RESULTS The detector exhibited highly linear mean signal response across the system operating range and agreed well with theoretical prediction, as did the system MTF and NPS. The DQE analyzed as a function of kilovolt (peak), exposure, detector threshold, and readout mode revealed important considerations for system optimization. The model also demonstrated the important implications of false counts from both additive electronic noise and charge sharing and highlighted the system design and operational parameters that most affect detector performance in the presence of such factors: for example, increasing the detector threshold from 0 to 100 (arbitrary units of pulse height threshold roughly equivalent to 0.5 and 6 keV energy threshold, respectively), increased the f50 (spatial-frequency at which the MTF falls to a value of 0.50) by ∼30% with corresponding improvement in DQE. The range in exposure and additive noise for which PCDs yield intrinsically higher DQE was quantified, showing performance advantages under conditions of very low-dose, high additive noise, and high fidelity rejection of coincident photons. CONCLUSIONS The model for PCD signal and noise performance agreed with measurements of detector signal, MTF, and NPS and provided a useful basis for understanding complex dependencies in PCD imaging performance and the potential advantages (and disadvantages) in comparison to EIDs as well as an important guide to task-based optimization in developing new PCD imaging systems.},

note = {Moses and Sylvia Greenfield Best Scientific Paper Award 2014 },

keywords = {-Awards-, Analysis, High-Fidelity Modeling, Photon Counting},

pubstate = {published},

tppubtype = {article}

}

@article{dang2014dpirple,

title = {dPIRPLE: a joint estimation framework for deformable registration and penalized-likelihood CT image reconstruction using prior images.},

author = {Hao Dang and Adam S. Wang and Marc S. Sussman and Jeffrey H. Siewerdsen and J. Webster Stayman },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4142353},

doi = {10.1088/0031-9155/59/17/4799},

issn = {1361-6560},

year  = {2014},

date = {2014-09-01},

journal = {Physics in medicine and biology},

volume = {59},

number = {17},

pages = {4799--826},

publisher = {IOP Publishing},

abstract = {Sequential imaging studies are conducted in many clinical scenarios. Prior images from previous studies contain a great deal of patient-specific anatomical information and can be used in conjunction with subsequent imaging acquisitions to maintain image quality while enabling radiation dose reduction (e.g., through sparse angular sampling, reduction in fluence, etc). However, patient motion between images in such sequences results in misregistration between the prior image and current anatomy. Existing prior-image-based approaches often include only a simple rigid registration step that can be insufficient for capturing complex anatomical motion, introducing detrimental effects in subsequent image reconstruction. In this work, we propose a joint framework that estimates the 3D deformation between an unregistered prior image and the current anatomy (based on a subsequent data acquisition) and reconstructs the current anatomical image using a model-based reconstruction approach that includes regularization based on the deformed prior image. This framework is referred to as deformable prior image registration, penalized-likelihood estimation (dPIRPLE). Central to this framework is the inclusion of a 3D B-spline-based free-form-deformation model into the joint registration-reconstruction objective function. The proposed framework is solved using a maximization strategy whereby alternating updates to the registration parameters and image estimates are applied allowing for improvements in both the registration and reconstruction throughout the optimization process. Cadaver experiments were conducted on a cone-beam CT testbench emulating a lung nodule surveillance scenario. Superior reconstruction accuracy and image quality were demonstrated using the dPIRPLE algorithm as compared to more traditional reconstruction methods including filtered backprojection, penalized-likelihood estimation (PLE), prior image penalized-likelihood estimation (PIPLE) without registration, and prior image penalized-likelihood estimation with rigid registration of a prior image (PIRPLE) over a wide range of sampling sparsity and exposure levels.},

keywords = {Image Registration, Lungs, MBIR, Prior Images, Sequential CT, Sparse Sampling},

pubstate = {published},

tppubtype = {article}

}

@article{Gang2014,

title = {Task-based detectability in CT image reconstruction by filtered backprojection and penalized likelihood estimation.},

author = {Grace Gang and J. Webster Stayman and Wojciech Zbijewski and Jeffrey H. Siewerdsen},

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4115652},

doi = {10.1118/1.4883816},

issn = {0094-2405},

year  = {2014},

date = {2014-08-01},

journal = {Medical physics},

volume = {41},

number = {8},

pages = {081902},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE Nonstationarity is an important aspect of imaging performance in CT and cone-beam CT (CBCT), especially for systems employing iterative reconstruction. This work presents a theoretical framework for both filtered-backprojection (FBP) and penalized-likelihood (PL) reconstruction that includes explicit descriptions of nonstationary noise, spatial resolution, and task-based detectability index. Potential utility of the model was demonstrated in the optimal selection of regularization parameters in PL reconstruction. METHODS Analytical models for local modulation transfer function (MTF) and noise-power spectrum (NPS) were investigated for both FBP and PL reconstruction, including explicit dependence on the object and spatial location. For FBP, a cascaded systems analysis framework was adapted to account for nonstationarity by separately calculating fluence and system gains for each ray passing through any given voxel. For PL, the point-spread function and covariance were derived using the implicit function theorem and first-order Taylor expansion according to Fessler ["Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): Applications to tomography," IEEE Trans. Image Process. 5(3), 493-506 (1996)]. Detectability index was calculated for a variety of simple tasks. The model for PL was used in selecting the regularization strength parameter to optimize task-based performance, with both a constant and a spatially varying regularization map. RESULTS Theoretical models of FBP and PL were validated in 2D simulated fan-beam data and found to yield accurate predictions of local MTF and NPS as a function of the object and the spatial location. The NPS for both FBP and PL exhibit similar anisotropic nature depending on the pathlength (and therefore, the object and spatial location within the object) traversed by each ray, with the PL NPS experiencing greater smoothing along directions with higher noise. The MTF of FBP is isotropic and independent of location to a first order approximation, whereas the MTF of PL is anisotropic in a manner complementary to the NPS. Task-based detectability demonstrates dependence on the task, object, spatial location, and smoothing parameters. A spatially varying regularization "map" designed from locally optimal regularization can improve overall detectability beyond that achievable with the commonly used constant regularization parameter. CONCLUSIONS Analytical models for task-based FBP and PL reconstruction are predictive of nonstationary noise and resolution characteristics, providing a valuable framework for understanding and optimizing system performance in CT and CBCT.},

keywords = {Analysis, Customized Acquisition, MBIR, Regularization Design, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{wang2014low,

title = {Low-dose preview for patient-specific, task-specific technique selection in cone-beam CT.},

author = {Adam S. Wang and J. Webster Stayman and Yoshito Otake and Sebastian Vogt and Gerhard Kleinszig and A. Jay Khanna and Gary L. Gallia and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4106458},

doi = {10.1118/1.4884039},

issn = {0094-2405},

year  = {2014},

date = {2014-07-01},

journal = {Medical physics},

volume = {41},

number = {7},

pages = {071915},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE A method is presented for generating simulated low-dose cone-beam CT (CBCT) preview images from which patient- and task-specific minimum-dose protocols can be confidently selected prospectively in clinical scenarios involving repeat scans. METHODS In clinical scenarios involving a series of CBCT images, the low-dose preview (LDP) method operates upon the first scan to create a projection dataset that accurately simulates the effects of dose reduction in subsequent scans by injecting noise of proper magnitude and correlation, including both quantum and electronic readout noise as important components of image noise in flat-panel detector CBCT. Experiments were conducted to validate the LDP method in both a head phantom and a cadaveric torso by performing CBCT acquisitions spanning a wide dose range (head: 0.8-13.2 mGy, body: 0.8-12.4 mGy) with a prototype mobile C-arm system. After injecting correlated noise to simulate dose reduction, the projections were reconstructed using both conventional filtered backprojection (FBP) and an iterative, model-based image reconstruction method (MBIR). The LDP images were then compared to real CBCT images in terms of noise magnitude, noise-power spectrum (NPS), spatial resolution, contrast, and artifacts. RESULTS For both FBP and MBIR, the LDP images exhibited accurate levels of spatial resolution and contrast that were unaffected by the correlated noise injection, as expected. Furthermore, the LDP image noise magnitude and NPS were in strong agreement with real CBCT images acquired at the corresponding, reduced dose level across the entire dose range considered. The noise magnitude agreed within 7% for both the head phantom and cadaveric torso, and the NPS showed a similar level of agreement up to the Nyquist frequency. Therefore, the LDP images were highly representative of real image quality across a broad range of dose and reconstruction methods. On the other hand, naïve injection ofuncorrelated noise resulted in strong underestimation of the true noise, which would lead to overly optimistic predictions of dose reduction. CONCLUSIONS Correlated noise injection is essential to accurate simulation of CBCT image quality at reduced dose. With the proposed LDP method, the user can prospectively select patient-specific, minimum-dose protocols (viz., acquisition technique and reconstruction method) suitable to a particular imaging task and to the user's own observer preferences for CBCT scans following the first acquisition. The method could provide dose reduction in common clinical scenarios involving multiple CBCT scans, such as image-guided surgery and radiotherapy.},

keywords = {Analysis, CBCT, Regularization Design, System Assessment},

pubstate = {published},

tppubtype = {article}

}

@article{carrino2013dedicated,

title = {Dedicated cone-beam CT system for extremity imaging.},

author = {John A. Carrino and Abdullah Al Muhit and Wojciech Zbijewski and Gaurav K. Thawait and J. Webster Stayman and Nathan Packard and Robert Senn and Dong Yang and David H. Foos and John Yorkston and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4263642},

doi = {10.1148/radiol.13130225},

issn = {1527-1315},

year  = {2014},

date = {2014-03-01},

journal = {Radiology},

volume = {270},

number = {3},

pages = {816--24},

publisher = {Radiological Society of North America},

abstract = {PURPOSE To provide initial assessment of image quality and dose for a cone-beam computed tomographic (CT) scanner dedicated to extremity imaging. MATERIALS AND METHODS A prototype cone-beam CT scanner has been developed for imaging the extremities, including the weight-bearing lower extremities. Initial technical assessment included evaluation of radiation dose measured as a function of kilovolt peak and tube output (in milliampere seconds), contrast resolution assessed in terms of the signal difference-to-noise ratio (SDNR), spatial resolution semiquantitatively assessed by using a line-pair module from a phantom, and qualitative evaluation of cadaver images for potential diagnostic value and image artifacts by an expert CT observer (musculoskeletal radiologist). RESULTS The dose for a nominal scan protocol (80 kVp, 108 mAs) was 9 mGy (absolute dose measured at the center of a CT dose index phantom). SDNR was maximized with the 80-kVp scan technique, and contrast resolution was sufficient for visualization of muscle, fat, ligaments and/or tendons, cartilage joint space, and bone. Spatial resolution in the axial plane exceeded 15 line pairs per centimeter. Streaks associated with x-ray scatter (in thicker regions of the patient--eg, the knee), beam hardening (about cortical bone--eg, the femoral shaft), and cone-beam artifacts (at joint space surfaces oriented along the scanning plane--eg, the interphalangeal joints) presented a slight impediment to visualization. Cadaver images (elbow, hand, knee, and foot) demonstrated excellent visibility of bone detail and good soft-tissue visibility suitable to a broad spectrum of musculoskeletal indications. CONCLUSION A dedicated extremity cone-beam CT scanner capable of imaging upper and lower extremities (including weight-bearing examinations) provides sufficient image quality and favorable dose characteristics to warrant further evaluation for clinical use.},

keywords = {CBCT, Extremities, System Assessment},

pubstate = {published},

tppubtype = {article}

}

@article{sarapatahigh,

title = {High energy x-ray phase contrast CT using glancing-angle grating interferometers.},

author = {Adrian Sarapata and J. Webster Stayman and Michael Finkenthal and Jeffrey H. Siewerdsen and Franz Pfeiffer and Dan Stutman},

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3981561},

doi = {10.1118/1.4860275},

issn = {0094-2405},

year  = {2014},

date = {2014-02-01},

journal = {Medical physics},

volume = {41},

number = {2},

pages = {021904},

abstract = {PURPOSE The authors present initial progress toward a clinically compatible x-ray phase contrast CT system, using glancing-angle x-ray grating interferometry to provide high contrast soft tissue images at estimated by computer simulation dose levels comparable to conventional absorption based CT. METHODS DPC-CT scans of a joint phantom and of soft tissues were performed in order to answer several important questions from a clinical setup point of view. A comparison between high and low fringe visibility systems is presented. The standard phase stepping method was compared with sliding window interlaced scanning. Using estimated dose values obtained with a Monte-Carlo code the authors studied the dependence of the phase image contrast on exposure time and dose. RESULTS Using a glancing angle interferometer at high x-ray energy (∼ 45 keV mean value) in combination with a conventional x-ray tube the authors achieved fringe visibility values of nearly 50%, never reported before. High fringe visibility is shown to be an indispensable parameter for a potential clinical scanner. Sliding window interlaced scanning proved to have higher SNRs and CNRs in a region of interest and to also be a crucial part of a low dose CT system. DPC-CT images of a soft tissue phantom at exposures in the range typical for absorption based CT of musculoskeletal extremities were obtained. Assuming a human knee as the CT target, good soft tissue phase contrast could be obtained at an estimated absorbed dose level around 8 mGy, similar to conventional CT. CONCLUSIONS DPC-CT with glancing-angle interferometers provides improved soft tissue contrast over absorption CT even at clinically compatible dose levels (estimated by a Monte-Carlo computer simulation). Further steps in image processing, data reconstruction, and spectral matching could make the technique fully clinically compatible. Nevertheless, due to its increased scan time and complexity the technique should be thought of not as replacing, but as complimentary to conventional CT, to be used in specific applications.},

keywords = {Phase-Contrast CT},

pubstate = {published},

tppubtype = {article}

}

@article{zbijewski2014dual,

title = {Dual-energy cone-beam CT with a flat-panel detector: effect of reconstruction algorithm on material classification.},

author = {Wojciech Zbijewski and Grace Gang and Jennifer Xu and Adam S. Wang and J. Webster Stayman and Katsuyuki Taguchi and John A. Carrino and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3977791},

doi = {10.1118/1.4863598},

issn = {0094-2405},

year  = {2014},

date = {2014-02-01},

journal = {Medical physics},

volume = {41},

number = {2},

pages = {021908},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE Cone-beam CT (CBCT) with a flat-panel detector (FPD) is finding application in areas such as breast and musculoskeletal imaging, where dual-energy (DE) capabilities offer potential benefit. The authors investigate the accuracy of material classification in DE CBCT using filtered backprojection (FBP) and penalized likelihood (PL) reconstruction and optimize contrast-enhanced DE CBCT of the joints as a function of dose, material concentration, and detail size. METHODS Phantoms consisting of a 15 cm diameter water cylinder with solid calcium inserts (50-200 mg/ml, 3-28.4 mm diameter) and solid iodine inserts (2-10 mg/ml, 3-28.4 mm diameter), as well as a cadaveric knee with intra-articular injection of iodine were imaged on a CBCT bench with a Varian 4343 FPD. The low energy (LE) beam was 70 kVp (+0.2 mm Cu), and the high energy (HE) beam was 120 kVp (+0.2 mm Cu, +0.5 mm Ag). Total dose (LE+HE) was varied from 3.1 to 15.6 mGy with equal dose allocation. Image-based DE classification involved a nearest distance classifier in the space of LE versus HE attenuation values. Recognizing the differences in noise between LE and HE beams, the LE and HE data were differentially filtered (in FBP) or regularized (in PL). Both a quadratic (PLQ) and a total-variation penalty (PLTV) were investigated for PL. The performance of DE CBCT material discrimination was quantified in terms of voxelwise specificity, sensitivity, and accuracy. RESULTS Noise in the HE image was primarily responsible for classification errors within the contrast inserts, whereas noise in the LE image mainly influenced classification in the surrounding water. For inserts of diameter 28.4 mm, DE CBCT reconstructions were optimized to maximize the total combined accuracy across the range of calcium and iodine concentrations, yielding values of ∼ 88% for FBP and PLQ, and ∼ 95% for PLTV at 3.1 mGy total dose, increasing to ∼ 95% for FBP and PLQ, and ∼ 98% for PLTV at 15.6 mGy total dose. For a fixed iodine concentration of 5 mg/ml and reconstructions maximizing overall accuracy across the range of insert diameters, the minimum diameter classified with accuracy textgreater80% was ∼ 15 mm for FBP and PLQ and ∼ 10 mm for PLTV, improving to ∼ 7 mm for FBP and PLQ and ∼ 3 mm for PLTV at 15.6 mGy. The results indicate similar performance for FBP and PLQ and showed improved classification accuracy with edge-preserving PLTV. A slight preference for increased smoothing of the HE data was found. DE CBCT discrimination of iodine and bone in the knee was demonstrated with FBP and PLTV at 6.2 mGy total dose. CONCLUSIONS For iodine concentrations textgreater5 mg/ml and detail size ∼ 20 mm, material classification accuracy of textgreater90% was achieved in DE CBCT with both FBP and PL at total doses textless10 mGy. Optimal performance was attained by selection of reconstruction parameters based on the differences in noise between HE and LE data, typically favoring stronger smoothing of the HE data, and by using penalties matched to the imaging task (e.g., edge-preserving PLTV in areas of uniform enhancement).},

keywords = {CBCT, MBIR, Spectral X-ray/CT},

pubstate = {published},

tppubtype = {article}

}

@article{wang2014soft,

title = {Soft-tissue imaging with C-arm cone-beam CT using statistical reconstruction.},

author = {Adam S. Wang and J. Webster Stayman and Yoshito Otake and Gerhard Kleinszig and Sebastian Vogt and Gary L. Gallia and A. Jay Khanna and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4046706},

doi = {10.1088/0031-9155/59/4/1005},

issn = {1361-6560},

year  = {2014},

date = {2014-02-01},

journal = {Physics in medicine and biology},

volume = {59},

number = {4},

pages = {1005--26},

publisher = {IOP Publishing},

abstract = {The potential for statistical image reconstruction methods such as penalized-likelihood (PL) to improve C-arm cone-beam CT (CBCT) soft-tissue visualization for intraoperative imaging over conventional filtered backprojection (FBP) is assessed in this work by making a fair comparison in relation to soft-tissue performance. A prototype mobile C-arm was used to scan anthropomorphic head and abdomen phantoms as well as a cadaveric torso at doses substantially lower than typical values in diagnostic CT, and the effects of dose reduction via tube current reduction and sparse sampling were also compared. Matched spatial resolution between PL and FBP was determined by the edge spread function of low-contrast (∼ 40-80 HU) spheres in the phantoms, which were representative of soft-tissue imaging tasks. PL using the non-quadratic Huber penalty was found to substantially reduce noise relative to FBP, especially at lower spatial resolution where PL provides a contrast-to-noise ratio increase up to 1.4-2.2 × over FBP at 50% dose reduction across all objects. Comparison of sampling strategies indicates that soft-tissue imaging benefits from fully sampled acquisitions at dose above ∼ 1.7 mGy and benefits from 50% sparsity at dose below ∼ 1.0 mGy. Therefore, an appropriate sampling strategy along with the improved low-contrast visualization offered by statistical reconstruction demonstrates the potential for extending intraoperative C-arm CBCT to applications in soft-tissue interventions in neurosurgery as well as thoracic and abdominal surgeries by overcoming conventional tradeoffs in noise, spatial resolution, and dose.},

keywords = {CBCT, Head/Neck, MBIR, System Assessment},

pubstate = {published},

tppubtype = {article}

}

@article{Otake2013,

title = {Robust 3D-2D image registration: application to spine interventions and vertebral labeling in the presence of anatomical deformation.},

author = {Yoshito Otake and Adam S. Wang and J. Webster Stayman and Ali Uneri and Gerhard Kleinszig and Sebastian Vogt and A. Jay Khanna and Ziya L. Gokaslan and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4915373},

doi = {10.1088/0031-9155/58/23/8535},

issn = {1361-6560},

year  = {2013},

date = {2013-12-01},

journal = {Physics in medicine and biology},

volume = {58},

number = {23},

pages = {8535--53},

abstract = {We present a framework for robustly estimating registration between a 3D volume image and a 2D projection image and evaluate its precision and robustness in spine interventions for vertebral localization in the presence of anatomical deformation. The framework employs a normalized gradient information similarity metric and multi-start covariance matrix adaptation evolution strategy optimization with local-restarts, which provided improved robustness against deformation and content mismatch. The parallelized implementation allowed orders-of-magnitude acceleration in computation time and improved the robustness of registration via multi-start global optimization. Experiments involved a cadaver specimen and two CT datasets (supine and prone) and 36 C-arm fluoroscopy images acquired with the specimen in four positions (supine, prone, supine with lordosis, prone with kyphosis), three regions (thoracic, abdominal, and lumbar), and three levels of geometric magnification (1.7, 2.0, 2.4). Registration accuracy was evaluated in terms of projection distance error (PDE) between the estimated and true target points in the projection image, including 14 400 random trials (200 trials on the 72 registration scenarios) with initialization error up to ±200 mm and ±10°. The resulting median PDE was better than 0.1 mm in all cases, depending somewhat on the resolution of input CT and fluoroscopy images. The cadaver experiments illustrated the tradeoff between robustness and computation time, yielding a success rate of 99.993% in vertebral labeling (with 'success' defined as PDE textless5 mm) using 1,718 664 ± 96 582 function evaluations computed in 54.0 ± 3.5 s on a mid-range GPU (nVidia, GeForce GTX690). Parameters yielding a faster search (e.g., fewer multi-starts) reduced robustness under conditions of large deformation and poor initialization (99.535% success for the same data registered in 13.1 s), but given good initialization (e.g., ±5 mm, assuming a robust initial run) the same registration could be solved with 99.993% success in 6.3 s. The ability to register CT to fluoroscopy in a manner robust to patient deformation could be valuable in applications such as radiation therapy, interventional radiology, and an assistant to target localization (e.g., vertebral labeling) in image-guided spine surgery.},

keywords = {CBCT, Image Registration, Spine},

pubstate = {published},

tppubtype = {article}

}

@article{Stayman2013b,

title = {PIRPLE: a penalized-likelihood framework for incorporation of prior images in CT reconstruction.},

author = {J. Webster Stayman and Hao Dang and Yifu Ding and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3868341},

doi = {10.1088/0031-9155/58/21/7563},

issn = {1361-6560},

year  = {2013},

date = {2013-11-01},

journal = {Physics in medicine and biology},

volume = {58},

number = {21},

pages = {7563--82},

abstract = {Over the course of diagnosis and treatment, it is common for a number of imaging studies to be acquired. Such imaging sequences can provide substantial patient-specific prior knowledge about the anatomy that can be incorporated into a prior-image-based tomographic reconstruction for improved image quality and better dose utilization. We present a general methodology using a model-based reconstruction approach including formulations of the measurement noise that also integrates prior images. This penalized-likelihood technique adopts a sparsity enforcing penalty that incorporates prior information yet allows for change between the current reconstruction and the prior image. Moreover, since prior images are generally not registered with the current image volume, we present a modified model-based approach that seeks a joint registration of the prior image in addition to the reconstruction of projection data. We demonstrate that the combined prior-image- and model-based technique outperforms methods that ignore the prior data or lack a noise model. Moreover, we demonstrate the importance of registration for prior-image-based reconstruction methods and show that the prior-image-registered penalized-likelihood estimation (PIRPLE) approach can maintain a high level of image quality in the presence of noisy and undersampled projection data.},

keywords = {Image Registration, MBIR, Prior Images, Sequential CT},

pubstate = {published},

tppubtype = {article}

}

@article{Sisniega2013,

title = {Monte Carlo study of the effects of system geometry and antiscatter grids on cone-beam CT scatter distributions.},

author = {Alejandro Sisniega and Wojciech Zbijewski and Andreu Badal and Iacovos S. Kyprianou and J. Webster Stayman and Juan J. Vaquero and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3651212},

doi = {10.1118/1.4801895},

issn = {0094-2405},

year  = {2013},

date = {2013-05-01},

journal = {Medical physics},

volume = {40},

number = {5},

pages = {051915},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE The proliferation of cone-beam CT (CBCT) has created interest in performance optimization, with x-ray scatter identified among the main limitations to image quality. CBCT often contends with elevated scatter, but the wide variety of imaging geometry in different CBCT configurations suggests that not all configurations are affected to the same extent. Graphics processing unit (GPU) accelerated Monte Carlo (MC) simulations are employed over a range of imaging geometries to elucidate the factors governing scatter characteristics, efficacy of antiscatter grids, guide system design, and augment development of scatter correction. METHODS A MC x-ray simulator implemented on GPU was accelerated by inclusion of variance reduction techniques (interaction splitting, forced scattering, and forced detection) and extended to include x-ray spectra and analytical models of antiscatter grids and flat-panel detectors. The simulator was applied to small animal (SA), musculoskeletal (MSK) extremity, otolaryngology (Head), breast, interventional C-arm, and on-board (kilovoltage) linear accelerator (Linac) imaging, with an axis-to-detector distance (ADD) of 5, 12, 22, 32, 60, and 50 cm, respectively. Each configuration was modeled with and without an antiscatter grid and with (i) an elliptical cylinder varying 70-280 mm in major axis; and (ii) digital murine and anthropomorphic models. The effects of scatter were evaluated in terms of the angular distribution of scatter incident upon the detector, scatter-to-primary ratio (SPR), artifact magnitude, contrast, contrast-to-noise ratio (CNR), and visual assessment. RESULTS Variance reduction yielded improvements in MC simulation efficiency ranging from ∼17-fold (for SA CBCT) to ∼35-fold (for Head and C-arm), with the most significant acceleration due to interaction splitting (∼6 to ∼10-fold increase in efficiency). The benefit of a more extended geometry was evident by virtue of a larger air gap-e.g., for a 16 cm diameter object, the SPR reduced from 1.5 for ADD = 12 cm (MSK geometry) to 1.1 for ADD = 22 cm (Head) and to 0.5 for ADD = 60 cm (C-arm). Grid efficiency was higher for configurations with shorter air gap due to a broader angular distribution of scattered photons-e.g., scatter rejection factor ∼0.8 for MSK geometry versus ∼0.65 for C-arm. Grids reduced cupping for all configurations but had limited improvement on scatter-induced streaks and resulted in a loss of CNR for the SA, Breast, and C-arm. Relative contribution of forward-directed scatter increased with a grid (e.g., Rayleigh scatter fraction increasing from ∼0.15 without a grid to ∼0.25 with a grid for the MSK configuration), resulting in scatter distributions with greater spatial variation (the form of which depended on grid orientation). CONCLUSIONS A fast MC simulator combining GPU acceleration with variance reduction provided a systematic examination of a range of CBCT configurations in relation to scatter, highlighting the magnitude and spatial uniformity of individual scatter components, illustrating tradeoffs in CNR and artifacts and identifying the system geometries for which grids are more beneficial (e.g., MSK) from those in which an extended geometry is the better defense (e.g., C-arm head imaging). Compact geometries with an antiscatter grid challenge assumptions of slowly varying scatter distributions due to increased contribution of Rayleigh scatter.},

keywords = {CBCT, Scatter Estimation, System Assessment},

pubstate = {published},

tppubtype = {article}

}

@article{uneri2013deformable,

title = {Deformable registration of the inflated and deflated lung in cone-beam CT-guided thoracic surgery: initial investigation of a combined model- and image-driven approach.},

author = {Ali Uneri and Sajendra Nithiananthan and Sebastian Schafer and Yoshito Otake and J. Webster Stayman and Gerhard Kleinszig and Marc S. Sussman and Jerry L. Prince and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3537709},

doi = {10.1118/1.4767757},

issn = {0094-2405},

year  = {2013},

date = {2013-01-01},

journal = {Medical physics},

volume = {40},

number = {1},

pages = {017501},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE Surgical resection is the preferred modality for curative treatment of early stage lung cancer, but localization of small tumors (textless10 mm diameter) during surgery presents a major challenge that is likely to increase as more early-stage disease is detected incidentally and in low-dose CT screening. To overcome the difficulty of manual localization (fingers inserted through intercostal ports) and the cost, logistics, and morbidity of preoperative tagging (coil or dye placement under CT-fluoroscopy), the authors propose the use of intraoperative cone-beam CT (CBCT) and deformable image registration to guide targeting of small tumors in video-assisted thoracic surgery (VATS). A novel algorithm is reported for registration of the lung from its inflated state (prior to pleural breach) to the deflated state (during resection) to localize surgical targets and adjacent critical anatomy. METHODS The registration approach geometrically resolves images of the inflated and deflated lung using a coarse model-driven stage followed by a finer image-driven stage. The model-driven stage uses image features derived from the lung surfaces and airways: triangular surface meshes are morphed to capture bulk motion; concurrently, the airways generate graph structures from which corresponding nodes are identified. Interpolation of the sparse motion fields computed from the bounding surface and interior airways provides a 3D motion field that coarsely registers the lung and initializes the subsequent image-driven stage. The image-driven stage employs an intensity-corrected, symmetric form of the Demons method. The algorithm was validated over 12 datasets, obtained from porcine specimen experiments emulating CBCT-guided VATS. Geometric accuracy was quantified in terms of target registration error (TRE) in anatomical targets throughout the lung, and normalized cross-correlation. Variations of the algorithm were investigated to study the behavior of the model- and image-driven stages by modifying individual algorithmic steps and examining the effect in comparison to the nominal process. RESULTS The combined model- and image-driven registration process demonstrated accuracy consistent with the requirements of minimally invasive VATS in both target localization (∼3-5 mm within the target wedge) and critical structure avoidance (∼1-2 mm). The model-driven stage initialized the registration to within a median TRE of 1.9 mm (95% confidence interval (CI) maximum = 5.0 mm), while the subsequent image-driven stage yielded higher accuracy localization with 0.6 mm median TRE (95% CI maximum = 4.1 mm). The variations assessing the individual algorithmic steps elucidated the role of each step and in some cases identified opportunities for further simplification and improvement in computational speed. CONCLUSIONS The initial studies show the proposed registration method to successfully register CBCT images of the inflated and deflated lung. Accuracy appears sufficient to localize the target and adjacent critical anatomy within ∼1-2 mm and guide localization under conditions in which the target cannot be discerned directly in CBCT (e.g., subtle, nonsolid tumors). The ability to directly localize tumors in the operating room could provide a valuable addition to the VATS arsenal, obviate the cost, logistics, and morbidity of preoperative tagging, and improve patient safety. Future work includes in vivo testing, optimization of workflow, and integration with a CBCT image guidance system.},

keywords = {CBCT, Image Registration, Lungs},

pubstate = {published},

tppubtype = {article}

}

@article{Stayman2012a,

title = {Model-based tomographic reconstruction of objects containing known components.},

author = {J. Webster Stayman and Yoshito Otake and Jerry L. Prince and A. Jay Khanna and Jeffrey H. Siewerdsen},

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4503263},

doi = {10.1109/TMI.2012.2199763},

issn = {1558-254X},

year  = {2012},

date = {2012-10-01},

journal = {IEEE transactions on medical imaging},

volume = {31},

number = {10},

pages = {1837--48},

abstract = {The likelihood of finding manufactured components (surgical tools, implants, etc.) within a tomographic field-of-view has been steadily increasing. One reason is the aging population and proliferation of prosthetic devices, such that more people undergoing diagnostic imaging have existing implants, particularly hip and knee implants. Another reason is that use of intraoperative imaging (e.g., cone-beam CT) for surgical guidance is increasing, wherein surgical tools and devices such as screws and plates are placed within or near to the target anatomy. When these components contain metal, the reconstructed volumes are likely to contain severe artifacts that adversely affect the image quality in tissues both near and far from the component. Because physical models of such components exist, there is a unique opportunity to integrate this knowledge into the reconstruction algorithm to reduce these artifacts. We present a model-based penalized-likelihood estimation approach that explicitly incorporates known information about component geometry and composition. The approach uses an alternating maximization method that jointly estimates the anatomy and the position and pose of each of the known components. We demonstrate that the proposed method can produce nearly artifact-free images even near the boundary of a metal implant in simulated vertebral pedicle screw reconstructions and even under conditions of substantial photon starvation. The simultaneous estimation of device pose also provides quantitative information on device placement that could be valuable to quality assurance and verification of treatment delivery.},

keywords = {Artifact Correction, Image Registration, Known Components, MBIR, Metal Artifacts, Spine},

pubstate = {published},

tppubtype = {article}

}

@article{dang2012robust,

title = {Robust methods for automatic image-to-world registration in cone-beam CT interventional guidance.},

author = {Hao Dang and Yoshito Otake and Sebastian Schafer and J. Webster Stayman and Gerhard Kleinszig and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3477200},

doi = {10.1118/1.4754589},

issn = {0094-2405},

year  = {2012},

date = {2012-10-01},

journal = {Medical physics},

volume = {39},

number = {10},

pages = {6484--98},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE Real-time surgical navigation relies on accurate image-to-world registration to align the coordinate systems of the image and patient. Conventional manual registration can present a workflow bottleneck and is prone to manual error and intraoperator variability. This work reports alternative means of automatic image-to-world registration, each method involving an automatic registration marker (ARM) used in conjunction with C-arm cone-beam CT (CBCT). The first involves a Known-Model registration method in which the ARM is a predefined tool, and the second is a Free-Form method in which the ARM is freely configurable. METHODS Studies were performed using a prototype C-arm for CBCT and a surgical tracking system. A simple ARM was designed with markers comprising a tungsten sphere within infrared reflectors to permit detection of markers in both x-ray projections and by an infrared tracker. The Known-Model method exercised a predefined specification of the ARM in combination with 3D-2D registration to estimate the transformation that yields the optimal match between forward projection of the ARM and the measured projection images. The Free-Form method localizes markers individually in projection data by a robust Hough transform approach extended from previous work, backprojected to 3D image coordinates based on C-arm geometric calibration. Image-domain point sets were transformed to world coordinates by rigid-body point-based registration. The robustness and registration accuracy of each method was tested in comparison to manual registration across a range of body sites (head, thorax, and abdomen) of interest in CBCT-guided surgery, including cases with interventional tools in the radiographic scene. RESULTS The automatic methods exhibited similar target registration error (TRE) and were comparable or superior to manual registration for placement of the ARM within ∼200 mm of C-arm isocenter. Marker localization in projection data was robust across all anatomical sites, including challenging scenarios involving the presence of interventional tools. The reprojection error of marker localization was independent of the distance of the ARM from isocenter, and the overall TRE was dominated by the configuration of individual fiducials and distance from the target as predicted by theory. The median TRE increased with greater ARM-to-isocenter distance (e.g., for the Free-Form method, TRE increasing from 0.78 mm to 2.04 mm at distances of ∼75 mm and 370 mm, respectively). The median TRE within ∼200 mm distance was consistently lower than that of the manual method (TRE = 0.82 mm). Registration performance was independent of anatomical site (head, thorax, and abdomen). The Free-Form method demonstrated a statistically significant improvement (p = 0.0044) in reproducibility compared to manual registration (0.22 mm versus 0.30 mm, respectively). CONCLUSIONS Automatic image-to-world registration methods demonstrate the potential for improved accuracy, reproducibility, and workflow in CBCT-guided procedures. A Free-Form method was shown to exhibit robustness against anatomical site, with comparable or improved TRE compared to manual registration. It was also comparable or superior in performance to a Known-Model method in which the ARM configuration is specified as a predefined tool, thereby allowing configuration of fiducials on the fly or attachment to the patient.},

keywords = {CBCT, Image Guided Surgery},

pubstate = {published},

tppubtype = {article}

}

@article{Nithiananthan2012,

title = {Extra-dimensional Demons: a method for incorporating missing tissue in deformable image registration.},

author = {Sajendra Nithiananthan and Sebastian Schafer and Daniel J. Mirota and J. Webster Stayman and Wojciech Zbijewski and Douglas D. Reh and Gary L. Gallia and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3443194},

doi = {10.1118/1.4747270},

issn = {0094-2405},

year  = {2012},

date = {2012-09-01},

journal = {Medical physics},

volume = {39},

number = {9},

pages = {5718--31},

abstract = {PURPOSE A deformable registration method capable of accounting for missing tissue (e.g., excision) is reported for application in cone-beam CT (CBCT)-guided surgical procedures. Excisions are identified by a segmentation step performed simultaneous to the registration process. Tissue excision is explicitly modeled by increasing the dimensionality of the deformation field to allow motion beyond the dimensionality of the image. The accuracy of the model is tested in phantom, simulations, and cadaver models. METHODS A variant of the Demons deformable registration algorithm is modified to include excision segmentation and modeling. Segmentation is performed iteratively during the registration process, with initial implementation using a threshold-based approach to identify voxels corresponding to "tissue" in the moving image and "air" in the fixed image. With each iteration of the Demons process, every voxel is assigned a probability of excision. Excisions are modeled explicitly during registration by increasing the dimensionality of the deformation field so that both deformations and excisions can be accounted for by in- and out-of-volume deformations, respectively. The out-of-volume (i.e., fourth) component of the deformation field at each voxel carries a magnitude proportional to the excision probability computed in the excision segmentation step. The registration accuracy of the proposed "extra-dimensional" Demons (XDD) and conventional Demons methods was tested in the presence of missing tissue in phantom models, simulations investigating the effect of excision size on registration accuracy, and cadaver studies emulating realistic deformations and tissue excisions imparted in CBCT-guided endoscopic skull base surgery. RESULTS Phantom experiments showed the normalized mutual information (NMI) in regions local to the excision to improve from 1.10 for the conventional Demons approach to 1.16 for XDD, and qualitative examination of the resulting images revealed major differences: the conventional Demons approach imparted unrealistic distortions in areas around tissue excision, whereas XDD provided accurate "ejection" of voxels within the excision site and maintained the registration accuracy throughout the rest of the image. Registration accuracy in areas far from the excision site (e.g., textgreater ∼5 mm) was identical for the two approaches. Quantitation of the effect was consistent in analysis of NMI, normalized cross-correlation (NCC), target registration error (TRE), and accuracy of voxels ejected from the volume (true-positive and false-positive analysis). The registration accuracy for conventional Demons was found to degrade steeply as a function of excision size, whereas XDD was robust in this regard. Cadaver studies involving realistic excision of the clivus, vidian canal, and ethmoid sinuses demonstrated similar results, with unrealistic distortion of anatomy imparted by conventional Demons and accurate ejection and deformation for XDD. CONCLUSIONS Adaptation of the Demons deformable registration process to include segmentation (i.e., identification of excised tissue) and an extra dimension in the deformation field provided a means to accurately accommodate missing tissue between image acquisitions. The extra-dimensional approach yielded accurate "ejection" of voxels local to the excision site while preserving the registration accuracy (typically subvoxel) of the conventional Demons approach throughout the rest of the image. The ability to accommodate missing tissue volumes is important to application of CBCT for surgical guidance (e.g., skull base drillout) and may have application in other areas of CBCT guidance.},

keywords = {CBCT, Image Guided Surgery, Image Registration},

pubstate = {published},

tppubtype = {article}

}

@article{Fredenberg2012,

title = {Ideal-observer detectability in photon-counting differential phase-contrast imaging using a linear-systems approach.},

author = {Erik Fredenberg and Mats Danielsson and J. Webster Stayman and Jeffrey H. Siewerdsen and Magnus Aslund},

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3427340},

doi = {10.1118/1.4739195},

issn = {0094-2405},

year  = {2012},

date = {2012-09-01},

journal = {Medical physics},

volume = {39},

number = {9},

pages = {5317--35},

abstract = {PURPOSE To provide a cascaded-systems framework based on the noise-power spectrum (NPS), modulation transfer function (MTF), and noise-equivalent number of quanta (NEQ) for quantitative evaluation of differential phase-contrast imaging (Talbot interferometry) in relation to conventional absorption contrast under equal-dose, equal-geometry, and, to some extent, equal-photon-economy constraints. The focus is a geometry for photon-counting mammography. METHODS Phase-contrast imaging is a promising technology that may emerge as an alternative or adjunct to conventional absorption contrast. In particular, phase contrast may increase the signal-difference-to-noise ratio compared to absorption contrast because the difference in phase shift between soft-tissue structures is often substantially larger than the absorption difference. We have developed a comprehensive cascaded-systems framework to investigate Talbot interferometry, which is a technique for differential phase-contrast imaging. Analytical expressions for the MTF and NPS were derived to calculate the NEQ and a task-specific ideal-observer detectability index under assumptions of linearity and shift invariance. Talbot interferometry was compared to absorption contrast at equal dose, and using either a plane wave or a spherical wave in a conceivable mammography geometry. The impact of source size and spectrum bandwidth was included in the framework, and the trade-off with photon economy was investigated in some detail. Wave-propagation simulations were used to verify the analytical expressions and to generate example images. RESULTS Talbot interferometry inherently detects the differential of the phase, which led to a maximum in NEQ at high spatial frequencies, whereas the absorption-contrast NEQ decreased monotonically with frequency. Further, phase contrast detects differences in density rather than atomic number, and the optimal imaging energy was found to be a factor of 1.7 higher than for absorption contrast. Talbot interferometry with a plane wave increased detectability for 0.1-mm tumor and glandular structures by a factor of 3-4 at equal dose, whereas absorption contrast was the preferred method for structures larger than ∼0.5 mm. Microcalcifications are small, but differ from soft tissue in atomic number more than density, which is favored by absorption contrast, and Talbot interferometry was barely beneficial at all within the resolution limit of the system. Further, Talbot interferometry favored detection of "sharp" as opposed to "smooth" structures, and discrimination tasks by about 50% compared to detection tasks. The technique was relatively insensitive to spectrum bandwidth, whereas the projected source size was more important. If equal photon economy was added as a restriction, phase-contrast efficiency was reduced so that the benefit for detection tasks almost vanished compared to absorption contrast, but discrimination tasks were still improved close to a factor of 2 at the resolution limit. CONCLUSIONS Cascaded-systems analysis enables comprehensive and intuitive evaluation of phase-contrast efficiency in relation to absorption contrast under requirements of equal dose, equal geometry, and equal photon economy. The benefit of Talbot interferometry was highly dependent on task, in particular detection versus discrimination tasks, and target size, shape, and material. Requiring equal photon economy weakened the benefit of Talbot interferometry in mammography.},

keywords = {Analysis, Phase-Contrast CT, Photon Counting},

pubstate = {published},

tppubtype = {article}

}

@article{reaungamornrat2012board,

title = {An on-board surgical tracking and video augmentation system for C-arm image guidance.},

author = {Sureerat Reaungamornrat and Yoshito Otake and Ali Uneri and Sebastian Schafer and Daniel J. Mirota and Sajendra Nithiananthan and J. Webster Stayman and Gerhard Kleinszig and A. Jay Khanna and Russell H. Taylor and Jeffrey H. Siewerdsen },

url = {http://www.ncbi.nlm.nih.gov/pubmed/22539008},

doi = {10.1007/s11548-012-0682-9},

issn = {1861-6429},

year  = {2012},

date = {2012-09-01},

journal = {International journal of computer assisted radiology and surgery},

volume = {7},

number = {5},

pages = {647--65},

publisher = {Springer-Verlag},

abstract = {PURPOSE Conventional tracker configurations for surgical navigation carry a variety of limitations, including limited geometric accuracy, line-of-sight obstruction, and mismatch of the view angle with the surgeon's-eye view. This paper presents the development and characterization of a novel tracker configuration (referred to as "Tracker-on-C") intended to address such limitations by incorporating the tracker directly on the gantry of a mobile C-arm for fluoroscopy and cone-beam CT (CBCT). METHODS A video-based tracker (MicronTracker, Claron Technology Inc., Toronto, ON, Canada) was mounted on the gantry of a prototype mobile isocentric C-arm next to the flat-panel detector. To maintain registration within a dynamically moving reference frame (due to rotation of the C-arm), a reference marker consisting of 6 faces (referred to as a "hex-face marker") was developed to give visibility across the full range of C-arm rotation. Three primary functionalities were investigated: surgical tracking, generation of digitally reconstructed radiographs (DRRs) from the perspective of a tracked tool or the current C-arm angle, and augmentation of the tracker video scene with image, DRR, and planning data. Target registration error (TRE) was measured in comparison with the same tracker implemented in a conventional in-room configuration. Graphics processing unit (GPU)-accelerated DRRs were generated in real time as an assistant to C-arm positioning (i.e., positioning the C-arm such that target anatomy is in the field-of-view (FOV)), radiographic search (i.e., a virtual X-ray projection preview of target anatomy without X-ray exposure), and localization (i.e., visualizing the location of the surgical target or planning data). Video augmentation included superimposing tracker data, the X-ray FOV, DRRs, planning data, preoperative images, and/or intraoperative CBCT onto the video scene. Geometric accuracy was quantitatively evaluated in each case, and qualitative assessment of clinical feasibility was analyzed by an experienced and fellowship-trained orthopedic spine surgeon within a clinically realistic surgical setup of the Tracker-on-C. RESULTS The Tracker-on-C configuration demonstrated improved TRE (0.87 ± 0.25) mm in comparison with a conventional in-room tracker setup (1.92 ± 0.71) mm (p textless 0.0001) attributed primarily to improved depth resolution of the stereoscopic camera placed closer to the surgical field. The hex-face reference marker maintained registration across the 180° C-arm orbit (TRE = 0.70 ± 0.32 mm). DRRs generated from the perspective of the C-arm X-ray detector demonstrated sub- mm accuracy (0.37 ± 0.20 mm) in correspondence with the real X-ray image. Planning data and DRRs overlaid on the video scene exhibited accuracy of (0.59 ± 0.38) pixels and (0.66 ± 0.36) pixels, respectively. Preclinical assessment suggested potential utility of the Tracker-on-C in a spectrum of interventions, including improved line of sight, an assistant to C-arm positioning, and faster target localization, while reducing X-ray exposure time. CONCLUSIONS The proposed tracker configuration demonstrated sub- mm TRE from the dynamic reference frame of a rotational C-arm through the use of the multi-face reference marker. Real-time DRRs and video augmentation from a natural perspective over the operating table assisted C-arm setup, simplified radiographic search and localization, and reduced fluoroscopy time. Incorporation of the proposed tracker configuration with C-arm CBCT guidance has the potential to simplify intraoperative registration, improve geometric accuracy, enhance visualization, and reduce radiation exposure.},

keywords = {CBCT, Image Guided Surgery, Multimodality},

pubstate = {published},

tppubtype = {article}

}

@article{otake2012automaticb,

title = {Automatic localization of vertebral levels in x-ray fluoroscopy using 3D-2D registration: a tool to reduce wrong-site surgery.},

author = {Yoshito Otake and Sebastian Schafer and J. Webster Stayman and Wojciech Zbijewski and Gerhard Kleinszig and Rainer Graumann and A. Jay Khanna and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3429949},

doi = {10.1088/0031-9155/57/17/5485},

issn = {1361-6560},

year  = {2012},

date = {2012-09-01},

journal = {Physics in medicine and biology},

volume = {57},

number = {17},

pages = {5485--508},

publisher = {IOP Publishing},

abstract = {Surgical targeting of the incorrect vertebral level (wrong-level surgery) is among the more common wrong-site surgical errors, attributed primarily to the lack of uniquely identifiable radiographic landmarks in the mid-thoracic spine. The conventional localization method involves manual counting of vertebral bodies under fluoroscopy, is prone to human error and carries additional time and dose. We propose an image registration and visualization system (referred to as LevelCheck), for decision support in spine surgery by automatically labeling vertebral levels in fluoroscopy using a GPU-accelerated, intensity-based 3D-2D (namely CT-to-fluoroscopy) registration. A gradient information (GI) similarity metric and a CMA-ES optimizer were chosen due to their robustness and inherent suitability for parallelization. Simulation studies involved ten patient CT datasets from which 50 000 simulated fluoroscopic images were generated from C-arm poses selected to approximate the C-arm operator and positioning variability. Physical experiments used an anthropomorphic chest phantom imaged under real fluoroscopy. The registration accuracy was evaluated as the mean projection distance (mPD) between the estimated and true center of vertebral levels. Trials were defined as successful if the estimated position was within the projection of the vertebral body (namely mPD textless5 mm). Simulation studies showed a success rate of 99.998% (1 failure in 50 000 trials) and computation time of 4.7 s on a midrange GPU. Analysis of failure modes identified cases of false local optima in the search space arising from longitudinal periodicity in vertebral structures. Physical experiments demonstrated the robustness of the algorithm against quantum noise and x-ray scatter. The ability to automatically localize target anatomy in fluoroscopy in near-real-time could be valuable in reducing the occurrence of wrong-site surgery while helping to reduce radiation exposure. The method is applicable beyond the specific case of vertebral labeling, since any structure defined in pre-operative (or intra-operative) CT or cone-beam CT can be automatically registered to the fluoroscopic scene.},

keywords = {CBCT, Image Guided Surgery, Image Registration, Multimodality, Spine},

pubstate = {published},

tppubtype = {article}

}

@article{lee2012intraoperative,

title = {Intraoperative C-arm cone-beam computed tomography: quantitative analysis of surgical performance in skull base surgery.},

author = {Stella Lee and Gary L. Gallia and Douglas D. Reh and Sebastian Schafer and Ali Uneri and Daniel J. Mirota and Sajendra Nithiananthan and Yoshito Otake and J. Webster Stayman and Wojciech Zbijewski and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3725328},

doi = {10.1002/lary.23374},

issn = {1531-4995},

year  = {2012},

date = {2012-09-01},

journal = {The Laryngoscope},

volume = {122},

number = {9},

pages = {1925--32},

publisher = {Wiley Subscription Services, Inc., A Wiley Company},

abstract = {OBJECTIVES/HYPOTHESIS To determine whether incorporation of intraoperative imaging via a new cone-beam computed tomography (CBCT) image-guidance system improves accuracy and facilitates resection in sinus and skull-base surgery through quantification of surgical performance. STUDY DESIGN Landmark identification and skull base ablation tasks were performed with a CBCT intraoperative image-guidance system in the experimental group and with image-guided surgery (IGS) alone based on preoperative computed tomography (CT) in the control group. METHODS Six cadaveric heads underwent preoperative CT imaging and surgical planning identifying surgical targets. Three types of surgical tasks were planned: landmark point identification, line contour identification, and volume drill-out. Key anatomic structures (carotid artery and optic nerve) were chosen for landmark identification and line contour tasks. Complete ethmoidectomy, vidian corridor drill-out, and clival resection were performed for volume ablation tasks. The CBCT guidance system was used in the experimental group and performance was assessed by metrics of target registration error, sensitivity, and specificity of excision. RESULTS Significant improvements were seen for point identification and line tracing tasks. Additional resection was performed in 67% of tasks in the CBCT group, and qualitative feedback indicated unequivocal improvement in confidence for all tasks. In review of tasks in the control group, additional resection would have been performed in 35% of tasks if an intraoperative image was available. CONCLUSIONS An experimental prototype C-arm CBCT guidance system was shown to improve surgical precision in the identification of skull base targets and increase accuracy in the ablation of surgical target volumes in comparison to using IGS alone.},

keywords = {CBCT, Head/Neck, Image Guided Surgery, System Assessment},

pubstate = {published},

tppubtype = {article}

}

@article{Gang2012,

title = {Cascaded systems analysis of noise and detectability in dual-energy cone-beam CT.},

author = {Grace Gang and Wojciech Zbijewski and J. Webster Stayman and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3422357},

doi = {10.1118/1.4736420},

issn = {0094-2405},

year  = {2012},

date = {2012-08-01},

journal = {Medical physics},

volume = {39},

number = {8},

pages = {5145--56},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE Dual-energy computed tomography and dual-energy cone-beam computed tomography (DE-CBCT) are promising modalities for applications ranging from vascular to breast, renal, hepatic, and musculoskeletal imaging. Accordingly, the optimization of imaging techniques for such applications would benefit significantly from a general theoretical description of image quality that properly incorporates factors of acquisition, reconstruction, and tissue decomposition in DE tomography. This work reports a cascaded systems analysis model that includes the Poisson statistics of x rays (quantum noise), detector model (flat-panel detectors), anatomical background, image reconstruction (filtered backprojection), DE decomposition (weighted subtraction), and simple observer models to yield a task-based framework for DE technique optimization. METHODS The theoretical framework extends previous modeling of DE projection radiography and CBCT. Signal and noise transfer characteristics are propagated through physical and mathematical stages of image formation and reconstruction. Dual-energy decomposition was modeled according to weighted subtraction of low- and high-energy images to yield the 3D DE noise-power spectrum (NPS) and noise-equivalent quanta (NEQ), which, in combination with observer models and the imaging task, yields the dual-energy detectability index (d(')). Model calculations were validated with NPS and NEQ measurements from an experimental imaging bench simulating the geometry of a dedicated musculoskeletal extremities scanner. Imaging techniques, including kVp pair and dose allocation, were optimized using d(') as an objective function for three example imaging tasks: (1) kidney stone discrimination; (2) iodine vs bone in a uniform, soft-tissue background; and (3) soft tissue tumor detection on power-law anatomical background. RESULTS Theoretical calculations of DE NPS and NEQ demonstrated good agreement with experimental measurements over a broad range of imaging conditions. Optimization results suggest a lower fraction of total dose imparted by the low-energy acquisition, a finding consistent with previous literature. The selection of optimal kVp pair reveals the combined effect of both quantum noise and contrast in the kidney stone discrimination and soft-tissue tumor detection tasks, whereas the K-edge effect of iodine was the dominant factor in determining kVp pairs in the iodine vs bone task. The soft-tissue tumor task illustrated the benefit of dual-energy imaging in eliminating anatomical background noise and improving detectability beyond that achievable by single-energy scans. CONCLUSIONS This work established a task-based theoretical framework that is predictive of DE image quality. The model can be utilized in optimizing a broad range of parameters in image acquisition, reconstruction, and decomposition, providing a useful tool for maximizing DE-CBCT image quality and reducing dose.},

keywords = {Analysis, Spectral X-ray/CT, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{Lee2012,

title = {Volume-of-change cone-beam CT for image-guided surgery.},

author = {Junghoon Lee and J. Webster Stayman and Yoshito Otake and Sebastian Schafer and Wojciech Zbijewski and A. Jay Khanna and Jerry L. Prince and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3432954},

doi = {10.1088/0031-9155/57/15/4969},

issn = {1361-6560},

year  = {2012},

date = {2012-08-01},

journal = {Physics in medicine and biology},

volume = {57},

number = {15},

pages = {4969--89},

abstract = {C-arm cone-beam CT (CBCT) can provide intraoperative 3D imaging capability for surgical guidance, but workflow and radiation dose are the significant barriers to broad utilization. One main reason is that each 3D image acquisition requires a complete scan with a full radiation dose to present a completely new 3D image every time. In this paper, we propose to utilize patient-specific CT or CBCT as prior knowledge to accurately reconstruct the aspects of the region that have changed by the surgical procedure from only a sparse set of x-rays. The proposed methods consist of a 3D-2D registration between the prior volume and a sparse set of intraoperative x-rays, creating digitally reconstructed radiographs (DRRs) from the registered prior volume, computing difference images by subtracting DRRs from the intraoperative x-rays, a penalized likelihood reconstruction of the volume of change (VOC) from the difference images, and finally a fusion of VOC reconstruction with the prior volume to visualize the entire surgical field. When the surgical changes are local and relatively small, the VOC reconstruction involves only a small volume size and a small number of projections, allowing less computation and lower radiation dose than is needed to reconstruct the entire surgical field. We applied this approach to sacroplasty phantom data obtained from a CBCT test bench and vertebroplasty data with a fresh cadaver acquired from a C-arm CBCT system with a flat-panel detector. The VOCs were reconstructed from a varying number of images (10-66 images) and compared to the CBCT ground truth using four different metrics (mean squared error, correlation coefficient, structural similarity index and perceptual difference model). The results show promising reconstruction quality with structural similarity to the ground truth close to 1 even when only 15-20 images were used, allowing dose reduction by the factor of 10-20.},

keywords = {CBCT, Image Guided Surgery, MBIR, Prior Images, Sparse Sampling, Spine},

pubstate = {published},

tppubtype = {article}

}

@article{schafer2012antiscatter,

title = {Antiscatter grids in mobile C-arm cone-beam CT: effect on image quality and dose.},

author = {Sebastian Schafer and J. Webster Stayman and Wojciech Zbijewski and Christian Schmidgunst and Gerhard Kleinszig and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3261054},

doi = {10.1118/1.3666947},

issn = {0094-2405},

year  = {2012},

date = {2012-01-01},

journal = {Medical physics},

volume = {39},

number = {1},

pages = {153--9},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE X-ray scatter is a major detriment to image quality in cone-beam CT (CBCT). Existing geometries exhibit strong differences in scatter susceptibility with more compact geometries, e.g., dental or musculoskeletal, benefiting from antiscatter grids, whereas in more extended geometries, e.g., IGRT, grid use carries tradeoffs in image quality per unit dose. This work assesses the tradeoffs in dose and image quality for grids applied in the context of low-dose CBCT on a mobile C-arm for image-guided surgery. METHODS Studies were performed on a mobile C-arm equipped with a flat-panel detector for high-quality CBCT. Antiscatter grids of grid ratio (GR) 6:1-12:1, 40 lp∕cm, were tested in "body" surgery, i.e., spine, using protocols for bone and soft-tissue visibility in the thoracic and abdominal spine. Studies focused on grid orientation, CT number accuracy, image noise, and contrast-to-noise ratio (CNR) in quantitative phantoms at constant dose. RESULTS There was no effect of grid orientation on possible gridline artifacts, given accurate angle-dependent gain calibration. Incorrect calibration was found to result in gridline shadows in the projection data that imparted high-frequency artifacts in 3D reconstructions. Increasing GR reduced errors in CT number from 31%, thorax, and 37%, abdomen, for gridless operation to 2% and 10%, respectively, with a 12:1 grid, while image noise increased by up to 70%. The CNR of high-contrast objects was largely unaffected by grids, but low-contrast soft-tissues suffered reduction in CNR, 2%-65%, across the investigated GR at constant dose. CONCLUSIONS While grids improved CT number accuracy, soft-tissue CNR was reduced due to attenuation of primary radiation. CNR could be restored by increasing dose by factors of ~1.6-2.5 depending on GR, e.g., increase from 4.6 mGy for the thorax and 12.5 mGy for the abdomen without antiscatter grids to approximately 12 mGy and 30 mGy, respectively, with a high-GR grid. However, increasing the dose poses a significant impediment to repeat intraoperative CBCT and can cause the cumulative intraoperative dose to exceed that of a single diagnostic CT scan. This places the mobile C-arm in the category of extended CBCT geometries with sufficient air gap for which the tradeoffs between CNR and dose typically do not favor incorporation of an antiscatter grid.},

keywords = {CBCT, Scatter Estimation},

pubstate = {published},

tppubtype = {article}

}

@article{prakash2011task,

title = {Task-based modeling and optimization of a cone-beam CT scanner for musculoskeletal imaging.},

author = {Prakhar Prakash and Wojciech Zbijewski and Grace Gang and Yifu Ding and J. Webster Stayman and John Yorkston and John A. Carrino and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3208412},

doi = {10.1118/1.3633937},

issn = {0094-2405},

year  = {2011},

date = {2011-10-01},

journal = {Medical physics},

volume = {38},

number = {10},

pages = {5612--29},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE This work applies a cascaded systems model for cone-beam CT imaging performance to the design and optimization of a system for musculoskeletal extremity imaging. The model provides a quantitative guide to the selection of system geometry, source and detector components, acquisition techniques, and reconstruction parameters. METHODS The model is based on cascaded systems analysis of the 3D noise-power spectrum (NPS) and noise-equivalent quanta (NEQ) combined with factors of system geometry (magnification, focal spot size, and scatter-to-primary ratio) and anatomical background clutter. The model was extended to task-based analysis of detectability index (d') for tasks ranging in contrast and frequency content, and d' was computed as a function of system magnification, detector pixel size, focal spot size, kVp, dose, electronic noise, voxel size, and reconstruction filter to examine trade-offs and optima among such factors in multivariate analysis. The model was tested quantitatively versus the measured NPS and qualitatively in cadaver images as a function of kVp, dose, pixel size, and reconstruction filter under conditions corresponding to the proposed scanner. RESULTS The analysis quantified trade-offs among factors of spatial resolution, noise, and dose. System magnification (M) was a critical design parameter with strong effect on spatial resolution, dose, and x-ray scatter, and a fairly robust optimum was identified at M ∼ 1.3 for the imaging tasks considered. The results suggested kVp selection in the range of ∼65-90 kVp, the lower end (65 kVp) maximizing subject contrast and the upper end maximizing NEQ (90 kVp). The analysis quantified fairly intuitive results-e.g., ∼0.1-0.2 mm pixel size (and a sharp reconstruction filter) optimal for high-frequency tasks (bone detail) compared to ∼0.4 mm pixel size (and a smooth reconstruction filter) for low-frequency (soft-tissue) tasks. This result suggests a specific protocol for 1 × 1 (full-resolution) projection data acquisition followed by full-resolution reconstruction with a sharp filter for high-frequency tasks along with 2 × 2 binning reconstruction with a smooth filter for low-frequency tasks. The analysis guided selection of specific source and detector components implemented on the proposed scanner. The analysis also quantified the potential benefits and points of diminishing return in focal spot size, reduced electronic noise, finer detector pixels, and low-dose limits of detectability. Theoretical results agreed quantitatively with the measured NPS and qualitatively with evaluation of cadaver images by a musculoskeletal radiologist. CONCLUSIONS A fairly comprehensive model for 3D imaging performance in cone-beam CT combines factors of quantum noise, system geometry, anatomical background, and imaging task. The analysis provided a valuable, quantitative guide to design, optimization, and technique selection for a musculoskeletal extremities imaging system under development.},

keywords = {Analysis, CBCT, Extremities, System Design},

pubstate = {published},

tppubtype = {article}

}

@article{zbijewski2011dedicated,

title = {A dedicated cone-beam CT system for musculoskeletal extremities imaging: design, optimization, and initial performance characterization.},

author = {Wojciech Zbijewski and Paul De Jean and Prakhar Prakash and Yifu Ding and J. Webster Stayman and Nathan Packard and Robert Senn and Dong Yang and John Yorkston and Antonio Machado and John A. Carrino and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3172864},

doi = {10.1118/1.3611039},

issn = {0094-2405},

year  = {2011},

date = {2011-08-01},

journal = {Medical physics},

volume = {38},

number = {8},

pages = {4700--13},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE This paper reports on the design and initial imaging performance of a dedicated cone-beam CT (CBCT) system for musculoskeletal (MSK) extremities. The system complements conventional CT and MR and offers a variety of potential clinical and logistical advantages that are likely to be of benefit to diagnosis, treatment planning, and assessment of therapy response in MSK radiology, orthopaedic surgery, and rheumatology. METHODS The scanner design incorporated a host of clinical requirements (e.g., ability to scan the weight-bearing knee in a natural stance) and was guided by theoretical and experimental analysis of image quality and dose. Such criteria identified the following basic scanner components and system configuration: a flat-panel detector (FPD, Varian 3030+, 0.194 mm pixels); and a low-power, fixed anode x-ray source with 0.5 mm focal spot (SourceRay XRS-125-7K-P, 0.875 kW) mounted on a retractable C-arm allowing for two scanning orientations with the capability for side entry, viz. a standing configuration for imaging of weight-bearing lower extremities and a sitting configuration for imaging of tensioned upper extremity and unloaded lower extremity. Theoretical modeling employed cascaded systems analysis of modulation transfer function (MTF) and detective quantum efficiency (DQE) computed as a function of system geometry, kVp and filtration, dose, source power, etc. Physical experimentation utilized an imaging bench simulating the scanner geometry for verification of theoretical results and investigation of other factors, such as antiscatter grid selection and 3D image quality in phantom and cadaver, including qualitative comparison to conventional CT. RESULTS Theoretical modeling and benchtop experimentation confirmed the basic suitability of the FPD and x-ray source mentioned above. Clinical requirements combined with analysis of MTF and DQE yielded the following system geometry: a -55 cm source-to-detector distance; 1.3 magnification; a 20 cm diameter bore (20 x 20 x 20 cm3 field of view); total acquisition arc of -240 degrees. The system MTF declines to 50% at -1.3 mm(-1) and to 10% at -2.7 mm(-1), consistent with sub-millimeter spatial resolution. Analysis of DQE suggested a nominal technique of 90 kVp (+0.3 mm Cu added filtration) to provide high imaging performance from -500 projections at less than -0.5 kW power, implying -6.4 mGy (0.064 mSv) for low-dose protocols and -15 mGy (0.15 mSv) for high-quality protocols. The experimental studies show improved image uniformity and contrast-to-noise ratio (without increase in dose) through incorporation of a custom 10:1 GR antiscatter grid. Cadaver images demonstrate exquisite bone detail, visualization of articular morphology, and soft-tissue visibility comparable to diagnostic CT (10-20 HU contrast resolution). CONCLUSIONS The results indicate that the proposed system will deliver volumetric images of the extremities with soft-tissue contrast resolution comparable to diagnostic CT and improved spatial resolution at potentially reduced dose. Cascaded systems analysis provided a useful basis for system design and optimization without costly repeated experimentation. A combined process of design specification, image quality analysis, clinical feedback, and revision yielded a prototype that is now awaiting clinical pilot studies. Potential advantages of the proposed system include reduced space and cost, imaging of load-bearing extremities, and combined volumetric imaging with real-time fluoroscopy and digital radiography.},

keywords = {Analysis, CBCT, Extremities, System Assessment, System Design},

pubstate = {published},

tppubtype = {article}

}

@article{schafer2011mobile,

title = {Mobile C-arm cone-beam CT for guidance of spine surgery: image quality, radiation dose, and integration with interventional guidance.},

author = {Sebastian Schafer and Sajendra Nithiananthan and Daniel J. Mirota and Ali Uneri and J. Webster Stayman and Wojciech Zbijewski and Christian Schmidgunst and Gerhard Kleinszig and A. Jay Khanna and Jeffrey H. Siewerdsen },

url = {http://www.ncbi.nlm.nih.gov/pubmed/21928628 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3161502},

doi = {10.1118/1.3597566},

issn = {0094-2405},

year  = {2011},

date = {2011-08-01},

journal = {Medical physics},

volume = {38},

number = {8},

pages = {4563--74},

publisher = {American Association of Physicists in Medicine},

abstract = {PURPOSE A flat-panel detector based mobile isocentric C-arm for cone-beam CT (CBCT) has been developed to allow intraoperative 3D imaging with sub-millimeter spatial resolution and soft-tissue visibility. Image quality and radiation dose were evaluated in spinal surgery, commonly relying on lower-performance image intensifier based mobile C-arms. Scan protocols were developed for task-specific imaging at minimum dose, in-room exposure was evaluated, and integration of the imaging system with a surgical guidance system was demonstrated in preclinical studies of minimally invasive spine surgery. METHODS Radiation dose was assessed as a function of kilovolt (peak) (80-120 kVp) and milliampere second using thoracic and lumbar spine dosimetry phantoms. In-room radiation exposure was measured throughout the operating room for various CBCT scan protocols. Image quality was assessed using tissue-equivalent inserts in chest and abdomen phantoms to evaluate bone and soft-tissue contrast-to-noise ratio as a function of dose, and task-specific protocols (i.e., visualization of bone or soft-tissues) were defined. Results were applied in preclinical studies using a cadaveric torso simulating minimally invasive, transpedicular surgery. RESULTS Task-specific CBCT protocols identified include: thoracic bone visualization (100 kVp; 60 mAs; 1.8 mGy); lumbar bone visualization (100 kVp; 130 mAs; 3.2 mGy); thoracic soft-tissue visualization (100 kVp; 230 mAs; 4.3 mGy); and lumbar soft-tissue visualization (120 kVp; 460 mAs; 10.6 mGy)--each at (0.3 x 0.3 x 0.9 mm3) voxel size. Alternative lower-dose, lower-resolution soft-tissue visualization protocols were identified (100 kVp; 230 mAs; 5.1 mGy) for the lumbar region at (0.3 x 0.3 x 1.5 mm3) voxel size. Half-scan orbit of the C-arm (x-ray tube traversing under the table) was dosimetrically advantageous (prepatient attenuation) with a nonuniform dose distribution (-2 x higher at the entrance side than at isocenter, and -3-4 lower at the exit side). The in-room dose (microsievert) per unit scan dose (milligray) ranged from -21 microSv/mGy on average at tableside to -0.1 microSv/mGy at 2.0 m distance to isocenter. All protocols involve surgical staff stepping behind a shield wall for each CBCT scan, therefore imparting -zero dose to staff. Protocol implementation in preclinical cadaveric studies demonstrate integration of the C-arm with a navigation system for spine surgery guidance-specifically, minimally invasive vertebroplasty in which the system provided accurate guidance and visualization of needle placement and bone cement distribution. Cumulative dose including multiple intraoperative scans was -11.5 mGy for CBCT-guided thoracic vertebroplasty and -23.2 mGy for lumbar vertebroplasty, with dose to staff at tableside reduced to -1 min of fluoroscopy time (-4(0-60 microSv), compared to 5-11 min for the conventional approach. CONCLUSIONS Intraoperative CBCT using a high-performance mobile C-arm prototype demonstrates image quality suitable to guidance of spine surgery, with task-specific protocols providing an important basis for minimizing radiation dose, while maintaining image quality sufficient for surgical guidance. Images demonstrate a significant advance in spatial resolution and soft-tissue visibility, and CBCT guidance offers the potential to reduce fluoroscopy reliance, reducing cumulative dose to patient and staff. Integration with a surgical guidance system demonstrates precise tracking and visualization in up-to-date images (alleviating reliance on preoperative images only), including detection of errors or suboptimal surgical outcomes in the operating room.},

keywords = {CBCT, Image Guided Surgery, Spine, System Assessment},

pubstate = {published},

tppubtype = {article}

}

@article{Nithiananthan2011,

title = {Demons deformable registration of CT and cone-beam CT using an iterative intensity matching approach.},

author = {Sajendra Nithiananthan and Sebastian Schafer and Ali Uneri and Daniel J. Mirota and J. Webster Stayman and Wojciech Zbijewski and Kristy K. Brock and Michael J. Daly and Harley Chan and Jonathan C. Irish and Jeffrey H. Siewerdsen},

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3069990},

doi = {10.1118/1.3555037},

issn = {0094-2405},

year  = {2011},

date = {2011-04-01},

journal = {Medical physics},

volume = {38},

number = {4},

pages = {1785--98},

abstract = {PURPOSE A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values ("intensity"). METHODS A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specific intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and/or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. RESULTS The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to (2.5 +/- 2.8) mm compared to (3.5 +/- 3.0) mm with rigid registration. CONCLUSIONS A method was developed to iteratively correct CT-CBCT intensity disparity during Demons registration, enabling fast, intensity-based registration in CBCT-guided procedures such as surgery and radiotherapy, in which CBCT voxel values may be inaccurate. Accurate CT-CBCT registration in turn facilitates registration of multimodality preoperative image and planning data to intraoperative CBCT by way of the preoperative CT, thereby linking the intraoperative frame of reference to a wealth of preoperative information that could improve interventional guidance.},

keywords = {CBCT, Image Registration, Multimodality},

pubstate = {published},

tppubtype = {article}

}

@article{Gang2011,

title = {Analysis of Fourier-domain task-based detectability index in tomosynthesis and cone-beam CT in relation to human observer performance.},

author = {Grace Gang and Junghoon Lee and J. Webster Stayman and Daniel J. Mirota and Wojciech Zbijewski and Jerry L. Prince and Jeffrey H. Siewerdsen },

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3069989},

doi = {10.1118/1.3560428},

issn = {0094-2405},

year  = {2011},

date = {2011-04-01},

journal = {Medical physics},

volume = {38},

number = {4},

pages = {1754--68},

institution = {Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario M5G 2M9, Canada.},

abstract = {PURPOSE Design and optimization of medical imaging systems benefit from accurate theoretical modeling that identifies the physical factors governing image quality, particularly in the early stages of system development. This work extends Fourier metrics of imaging performance and detectability index (d') to tomosynthesis and cone-beam CT (CBCT) and investigates the extent to which d' is a valid descriptor of task-based imaging performance as assessed by human observers, METHODS The detectability index for tasks presented in 2D slices (d'(slice)) was derived from 3D cascaded systems analysis of tomosynthesis and CBCT. Anatomical background noise measured in a physical phantom presenting power-law spectral density was incorporated in the "generalized" noise-equivalent quanta. Theoretical calculations of d'(slice) were performed as a function of total angular extent (theta(tot)) of source-detector orbit ranging 10 degrees - 360 degrees under two acquisition schemes: (i) Constant angular separation between projections (constant-delta theta), giving variable number of projections (N(proj)) and dose vs theta(tot) and (ii) constant number of projections (constant-N(proj)), giving constant dose (but variable angular sampling) with theta(tot). Five simple observer models were investigated: Prewhitening (PW), prewhitening with eye filter and internal noise (PWEi), nonprewhitening (NPW), nonprewhitening with eye filter (NPWE), and nonprewhitening with eye filter and internal noise (NPWEi). Human observer performance was measured in 9AFC tests for five simple imaging tasks presented within uniform and power-law clutter backgrounds. Measurements (from 9AFC tests) and theoretical calculations (from cascaded systems analysis of d'(slice)) were compared in terms of area under the ROC curve (A(z)) RESULTS Reasonable correspondence between theoretical calculations and human observer performance was achieved for all imaging tasks over the broad range of experimental conditions and acquisition schemes. The PW and PWEi observer models tended to overestimate detectability, while the various NPW models predicted observer performance fairly well, with NPWEi giving the best overall agreement. Detectability was shown to increase with theta(tot) due to the reduction of out-of-plane clutter, reaching a plateau after a particular theta(tot) that depended on the imaging task. Depending on the acquisition scheme, however (i.e., constant-N(proj) or delta theta), detectability was seen in some cases to decline at higher theta(tot) due to tradeoffs among quantum noise, background clutter, and view sampling. CONCLUSIONS Generalized detectability index derived from a 3D cascaded systems model shows reasonable correspondence with human observer performance over a fairly broad range of imaging tasks and conditions, although discrepancies were observed in cases relating to orbits intermediate to 180 degrees and 360 degrees. The basic correspondence of theoretical and measured performance supports the application of such a theoretical framework for system design and optimization of tomosynthesis and CBCT.},

keywords = {Analysis, CBCT, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{reaungamornrat2011tracker,

title = {Tracker-on-C: A novel tracker configuration for image-guided therapy using a mobile C-arm},

author = {Sureerat Reaungamornrat and Yoshito Otake and Ali Uneri and Sebastian Schafer and J. Webster Stayman and Wojciech Zbijewski and Daniel J. Mirota and Jongheun Yoo and Sajendra Nithiananthan and A. Jay Khanna and Russell H. Taylor and Jeffrey H. Siewerdsen },

year  = {2011},

date = {2011-01-01},

journal = {Computer Assisted Radiology and Surgery, Berlin, Germany},

pages = {22--25},

keywords = {CBCT, Image Guided Surgery},

pubstate = {published},

tppubtype = {article}

}

@article{lee2011cone,

title = {Cone Beam CT-Assisted Endoscopic Sinus and Skull Base Surgery: Quantitative Analysis of Surgical Performance Using a Next-Generation C-Arm Prototype},

author = {Stella Lee and Gary L. Gallia and Douglas D. Reh and Sebastian Schafer and Ali Uneri and Daniel J. Mirota and Sajendra Nithiananthan and Yoshito Otake and J. Webster Stayman and Wojciech Zbijewski and Jeffrey H. Siewerdsen},

url = {http://www.thieme-connect.de/DOI/DOI?10.1055/s-2011-1274205},

doi = {10.1055/s-2011-1274205},

issn = {1531-5010},

year  = {2011},

date = {2011-01-01},

journal = {Skull Base},

volume = {21},

number = {S 01},

pages = {A030},

keywords = {CBCT, Head/Neck, Image Guided Surgery, System Assessment},

pubstate = {published},

tppubtype = {article}

}

@article{Stayman2004,

title = {Efficient calculation of resolution and covariance for penalized-likelihood reconstruction in fully 3-D SPECT.},

author = {J. Webster Stayman and Jeffrey A. Fessler },

url = {http://www.ncbi.nlm.nih.gov/pubmed/15575411},

doi = {10.1109/TMI.2004.837790},

issn = {0278-0062},

year  = {2004},

date = {2004-12-01},

journal = {IEEE transactions on medical imaging},

volume = {23},

number = {12},

pages = {1543--56},

abstract = {Resolution and covariance predictors have been derived previously for penalized-likelihood estimators. These predictors can provide accurate approximations to the local resolution properties and covariance functions for tomographic systems given a good estimate of the mean measurements. Although these predictors may be evaluated iteratively, circulant approximations are often made for practical computation times. However, when numerous evaluations are made repeatedly (as in penalty design or calculation of variance images), these predictors still require large amounts of computing time. In Stayman and Fessler (2000), we discussed methods for precomputing a large portion of the predictor for shift-invariant system geometries. In this paper, we generalize the efficient procedure discussed in Stayman and Fessler (2000) to shift-variant single photon emission computed tomography (SPECT) systems. This generalization relies on a new attenuation approximation and several observations on the symmetries in SPECT systems. These new general procedures apply to both two-dimensional and fully three-dimensional (3-D) SPECT models, that may be either precomputed and stored, or written in procedural form. We demonstrate the high accuracy of the predictions based on these methods using a simulated anthropomorphic phantom and fully 3-D SPECT system. The evaluation of these predictors requires significantly less computation time than traditional prediction techniques, once the system geometry specific precomputations have been made.},

keywords = {Analysis, Fast Algorithms, MBIR},

pubstate = {published},

tppubtype = {article}

}

@article{Stayman2004a,

title = {Compensation for nonuniform resolution using penalized-likelihood reconstruction in space-variant imaging systems.},

author = {J. Webster Stayman and Jeffrey A. Fessler },

url = {http://www.ncbi.nlm.nih.gov/pubmed/15027520},

doi = {10.1109/TMI.2003.823063},

issn = {0278-0062},

year  = {2004},

date = {2004-03-01},

journal = {IEEE transactions on medical imaging},

volume = {23},

number = {3},

pages = {269--84},

abstract = {Imaging systems that form estimates using a statistical approach generally yield images with nonuniform resolution properties. That is, the reconstructed images possess resolution properties marked by space-variant and/or anisotropic responses. We have previously developed a space-variant penalty for penalized-likelihood (PL) reconstruction that yields nearly uniform resolution properties. We demonstrated how to calculate this penalty efficiently and apply it to an idealized positron emission tomography (PET) system whose geometric response is space-invariant. In this paper, we demonstrate the efficient calculation and application of this penalty to space-variant systems. (The method is most appropriate when the system matrix has been precalculated.) We apply the penalty to a large field of view PET system where crystal penetration effects make the geometric response space-variant, and to a two-dimensional single photon emission computed tomography system whose detector responses are modeled by a depth-dependent Gaussian with linearly varying full-width at half-maximum. We perform a simulation study comparing reconstructions using our proposed PL approach with other reconstruction methods and demonstrate the relative resolution uniformity, and discuss tradeoffs among estimators that yield nearly uniform resolution. We observe similar noise performance for the PL and post-smoothed maximum-likelihood (ML) approaches with carefully matched resolution, so choosing one estimator over another should be made on other factors like computational complexity and convergence rates of the iterative reconstruction. Additionally, because the postsmoothed ML and the proposed PL approach can outperform one another in terms of resolution uniformity depending on the desired reconstruction resolution, we present and discuss a hybrid approach adopting both a penalty and post-smoothing.},

keywords = {Analysis, MBIR, Regularization Design},

pubstate = {published},

tppubtype = {article}

}

@article{stayman2000regularization,

title = {Regularization for uniform spatial resolution properties in penalized-likelihood image reconstruction.},

author = {J. Webster Stayman and Jeffrey A. Fessler },

url = {http://www.ncbi.nlm.nih.gov/pubmed/11026463},

doi = {10.1109/42.870666},

issn = {0278-0062},

year  = {2000},

date = {2000-06-01},

journal = {IEEE transactions on medical imaging},

volume = {19},

number = {6},

pages = {601--15},

publisher = {IEEE},

abstract = {Traditional space-invariant regularization methods in tomographic image reconstruction using penalized-likelihood estimators produce images with nonuniform spatial resolution properties. The local point spread functions that quantify the smoothing properties of such estimators are space-variant, asymmetric, and object-dependent even for space-invariant imaging systems. We propose a new quadratic regularization scheme for tomographic imaging systems that yields increased spatial uniformity and is motivated by the least-squares fitting of a parameterized local impulse response to a desired global response. We have developed computationally efficient methods for PET systems with shift-invariant geometric responses. We demonstrate the increased spatial uniformity of this new method versus conventional quadratic regularization schemes in simulated PET thorax scans.},

keywords = {Analysis, MBIR, Regularization Design},

pubstate = {published},

tppubtype = {article}

}