@article{Ma2024,

title = {Fully automatic online geometric calibration for non-circular cone-beam CT orbits using fiducials with unknown placement},

author = {Yiqun Ma and Tess Reynolds and Tina Ehtiati and Clifford Weiss and Kelvin Hong and Nick Theodore and Grace Gang and J. Webster Stayman},

url = {https://pubmed.ncbi.nlm.nih.gov/38573172/

https://aapm.onlinelibrary.wiley.com/doi/10.1002/mp.17041},

doi = {10.1002/mp.17041},

year  = {2024},

date = {2024-05-01},

urldate = {2024-05-01},

journal = {Medical Physics},

volume = {51},

issue = {5},

pages = {3245-3264},

keywords = {Customized Acquisition, Geometric Calibration},

pubstate = {published},

tppubtype = {article}

}

@article{Reynolds2023,

title = {Extended longitudinal and lateral 3D imaging with a continuous dual‐isocenter CBCT scan},

author = {Tess Reynolds and Sepideh Hatamikia and Yiqun Ma and Owen Dillon and Grace Gang and J. Webster Stayman and Ricky T O'Brien},

url = {https://aapm.onlinelibrary.wiley.com/doi/full/10.1002/mp.16234

https://pubmed.ncbi.nlm.nih.gov/36681083/},

doi = {10.1002/mp.16234},

year  = {2023},

date = {2023-04-01},

journal = {Medical Physics},

volume = {50},

issue = {4},

pages = {2372-2379},

keywords = {CBCT, Customized Acquisition, Spine},

pubstate = {published},

tppubtype = {article}

}

@article{Gang2022,

title = {Universal orbit design for metal artifact elimination},

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

url = {https://pubmed.ncbi.nlm.nih.gov/35472761/, https://iopscience.iop.org/article/10.1088/1361-6560/ac6aa0/meta},

doi = {10.1088/1361-6560/ac6aa0 },

year  = {2022},

date = {2022-05-23},

journal = {Physics in Medicine and Biology},

volume = {67},

issue = {11},

keywords = {Analysis, Customized Acquisition, Metal Artifacts},

pubstate = {published},

tppubtype = {article}

}

@article{Reynolds2022,

title = {Extended Intraoperative Longitudinal 3-Dimensional Cone Beam Computed Tomography Imaging With a Continuous Multi-Turn Reverse Helical Scan},

author = {Tess Reynolds and Yiqun Ma and Andrew J Kanawati and Alex Constantinidis and Zoe Williams and Grace Gang and Owen Dillon and Tom Russ and Wenying Wang and Tina Ehtiati and Clifford Weiss and Nick Theodore and Jeffrey H. Siewerdsen and J. Webster Stayman and Ricky T O'Brien},

url = {https://pubmed.ncbi.nlm.nih.gov/35510875/, https://journals.lww.com/investigativeradiology/Fulltext/2022/11000/Extended_Intraoperative_Longitudinal_3_Dimensional.7.aspx},

doi = {10.1097/RLI.0000000000000885 },

year  = {2022},

date = {2022-05-03},

journal = {Investigative Radiology},

volume = {57},

issue = {11},

keywords = {CBCT, Customized Acquisition, Spine},

pubstate = {published},

tppubtype = {article}

}

@article{Stayman2021,

title = {Spectral CT using a fine grid structure and varying x‐ray incidence angle},

author = {J. Webster Stayman and Matt Tivnan and Wenying Wang and Nadav Shapira and Grace Gang and Peter Noël},

url = {https://aapm.onlinelibrary.wiley.com/doi/full/10.1002/mp.14853

https://pubmed.ncbi.nlm.nih.gov/34151442/},

doi = {10.1002/mp.14853},

year  = {2021},

date = {2021-06-21},

journal = {Medical Physics},

abstract = {

},

keywords = {Customized Acquisition, Spectral X-ray/CT},

pubstate = {published},

tppubtype = {article}

}

@article{Wang2019d,

title = {Volume-of-interest Imaging with Dynamic Fluence Modulation Using Multiple Aperture Devices},

author = {Wenying Wang and Grace Gang and Jeffrey H. Siewerdsen and Reuven Levinson and Satomi Kawamoto and J. Webster Stayman},

url = {https://pubmed.ncbi.nlm.nih.gov/31528659/},

doi = {10.1117/1.JMI.6.3.033504},

year  = {2019},

date = {2019-09-01},

journal = {Journal of Medical Imaging},

volume = {6},

number = {3},

pages = {033504},

abstract = {Volume-of-interest (VOI) imaging is a strategy in computed tomography (CT) that restricts x-ray fluence to particular anatomical targets via dynamic beam modulation. This permits dose reduction while retaining image quality within the VOI. VOI-CT implementation has been challenged, in part, by a lack of hardware solutions for tailoring the incident fluence to the patient and anatomical site, as well as difficulties involving interior tomography reconstruction of truncated projection data. We propose a general VOI-CT imaging framework using multiple aperture devices (MADs), an emerging beam filtration scheme based on two binary x-ray filters. Location of the VOI is prescribed using two scout views at anterior-posterior (AP) and lateral perspectives. Based on a calibration of achievable fluence field patterns, MAD motion trajectories were designed using an optimization objective that seeks to maximize the relative fluence in the VOI subject to minimum fluence constraints. A modified penalized-likelihood method is developed for reconstruction of heavily truncated data using the full-field scout views to help solve the interior tomography problem. Physical experiments were conducted to show the feasibility of noncentered and elliptical VOI in two applications-spine and lung imaging. Improved dose utilization and retained image quality are validated with respect to standard full-field protocols. We observe that the contrast-to-noise ratio (CNR) is 40% higher compared with low-dose full-field scans at the same dose. The total dose reduction is 50% for equivalent image quality (CNR) within the VOI.},

keywords = {Customized Acquisition, Dynamic Bowtie, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{Gang2019b,

title = {Dynamic fluence field modulation in computed tomography using multiple aperture devices},

author = {Grace Gang and Andrew Mao and Wenying Wang and Jeffrey H. Siewerdsen and Aswin Mathews and Satomi Kawamoto and Reuven Levinson and J. Webster Stayman},

url = {https://iopscience.iop.org/article/10.1088/1361-6560/ab155e/meta},

doi = {10.1088/1361-6560/ab155e},

year  = {2019},

date = {2019-05-21},

journal = {Physics in Medicine and Biology},

volume = {64},

pages = {105024},

keywords = {Customized Acquisition, Dynamic Bowtie, System Design},

pubstate = {published},

tppubtype = {article}

}

@article{Stayman2019,

title = {Task-driven source–detector trajectories in cone-beam computed tomography: I. Theory and methods},

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

url = {https://www.spiedigitallibrary.org/journals/Journal-of-Medical-Imaging/volume-6/issue-2/025002/Task-driven-sourcedetector-trajectories-in-cone-beam-computed-tomography/10.1117/1.JMI.6.2.025002.full},

doi = {10.1117/1.JMI.6.2.025002},

year  = {2019},

date = {2019-05-02},

journal = {Journal of Medical Imaging},

volume = {6},

number = {2},

pages = {025002},

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

pubstate = {published},

tppubtype = {article}

}

@article{Capostagno2019,

title = {Task-driven source–detector trajectories in cone-beam computed tomography: II. Application to neuroradiology},

author = {Sarah Capostagno and J. Webster Stayman and Matthew W. Jacobson and Tina Ehtiati and Clifford Weiss and Jeffrey H. Siewerdsen },

url = {https://www.spiedigitallibrary.org/journals/Journal-of-Medical-Imaging/volume-6/issue-2/025004/Task-driven-sourcedetector-trajectories-in-cone-beam-computed-tomography/10.1117/1.JMI.6.2.025004.full},

doi = {10.1117/1.JMI.6.2.025004},

year  = {2019},

date = {2019-03-09},

journal = {Journal of Medical Imaging},

volume = {6},

number = {2},

pages = {025004},

keywords = {CBCT, Customized Acquisition, Head/Neck, Image Guided Surgery, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{Mao2018b,

title = {Dynamic fluence field modulation for miscentered patients in computed tomography},

author = {Andrew Mao and Grace Gang and William Shyr and Reuven Levinson and Jeffrey H. Siewerdsen and Satomi Kawamoto and J. Webster Stayman },

url = {https://www.spiedigitallibrary.org/journals/Journal-of-Medical-Imaging/volume-5/issue-4/043501/Dynamic-fluence-field-modulation-for-miscentered-patients-in-computed-tomography/10.1117/1.JMI.5.4.043501.full?SSO=1},

doi = {10.1117/1.JMI.5.4.043501},

year  = {2018},

date = {2018-10-24},

journal = {Journal of Medical Imaging},

volume = {5},

number = {4},

pages = {043501},

keywords = {Customized Acquisition, Dynamic Bowtie},

pubstate = {published},

tppubtype = {article}

}

@article{Jacobson2018,

title = {A line fiducial method for geometric calibration of cone-beam CT systems with diverse scan trajectories},

author = {Matthew W. Jacobson and Michael Ketcha and Sarah Capostagno and Andrew Martin and Ali Uneri and Joseph Goerres and Tharindu De Silva and Sureerat Reaungamornrat and Runze Han and Amir Manbachi and J. Webster Stayman and Sebastian Vogt and Gerhard Kleinszig and Jeffrey H. Siewerdsen},

url = {http://iopscience.iop.org/article/10.1088/1361-6560/aa9910/meta},

doi = {10.1088/1361-6560/aa9910},

year  = {2018},

date = {2018-01-15},

journal = {Physics in Medicine and Biology},

volume = {63},

number = {2},

pages = {025030},

keywords = {Customized Acquisition, Image Guided Surgery, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{Gang2017b,

title = {Task-driven optimization of fluence field and regularization for model-based iterative reconstruction in computed tomography},

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

url = {https://www.ncbi.nlm.nih.gov/pubmed/29035215

https://ieeexplore.ieee.org/document/8068249/},

doi = {10.1109/TMI.2017.2763538},

year  = {2017},

date = {2017-12-01},

journal = {IEEE Transactions on Medical Imaging},

volume = {36},

number = {12},

pages = {2424-35},

keywords = {Customized Acquisition, Dynamic Bowtie, Regularization Design, Task-Driven Imaging},

pubstate = {published},

tppubtype = {article}

}

@article{Gang2017b,

title = {Task-driven optimization of CT tube current modulation and regularization in model-based iterative reconstruction},

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

url = {https://www.ncbi.nlm.nih.gov/pubmed/28362638

http://stacks.iop.org/0031-9155/62/i=12/a=4777?key=crossref.b9662a9cb01ba6fc16efadc35de2e4b1},

doi = {10.1088/1361-6560/aa6a97},

issn = {0031-9155},

year  = {2017},

date = {2017-05-18},

journal = {Physics in Medicine and Biology},

volume = {62},

number = {12},

pages = {4777-4797},

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

pubstate = {published},

tppubtype = {article}

}

@article{Ouadah2016,

title = {Self-calibration of cone-beam CT geometry using 3D-2D image registration.},

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

url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4948745},

doi = {10.1088/0031-9155/61/7/2613},

issn = {1361-6560},

year  = {2016},

date = {2016-04-01},

journal = {Physics in medicine and biology},

volume = {61},

number = {7},

pages = {2613--32},

abstract = {Robotic C-arms are capable of complex orbits that can increase field of view, reduce artifacts, improve image quality, and/or reduce dose; however, it can be challenging to obtain accurate, reproducible geometric calibration required for image reconstruction for such complex orbits. This work presents a method for geometric calibration for an arbitrary source-detector orbit by registering 2D projection data to a previously acquired 3D image. It also yields a method by which calibration of simple circular orbits can be improved. The registration uses a normalized gradient information similarity metric and the covariance matrix adaptation-evolution strategy optimizer for robustness against local minima and changes in image content. The resulting transformation provides a 'self-calibration' of system geometry. The algorithm was tested in phantom studies using both a cone-beam CT (CBCT) test-bench and a robotic C-arm (Artis Zeego, Siemens Healthcare) for circular and non-circular orbits. Self-calibration performance was evaluated in terms of the full-width at half-maximum (FWHM) of the point spread function in CBCT reconstructions, the reprojection error (RPE) of steel ball bearings placed on each phantom, and the overall quality and presence of artifacts in CBCT images. In all cases, self-calibration improved the FWHM-e.g. on the CBCT bench},

keywords = {CBCT, Customized Acquisition, Geometric Calibration, Image Registration},

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{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{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}

}