@inproceedings{Sisniega2021,

title = {Deformable image-based motion compensation for interventional cone-beam CT with learned autofocus metrics},

author = {Alejandro Sisniega and Heyuan Huang and Wojciech Zbijewski and J. Webster Stayman and Clifford Weiss and Tina Ehtiati and Jeffrey H. Siewerdsen},

url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11595/115950W/Deformable-image-based-motion-compensation-for-interventional-cone-beam-CT/10.1117/12.2582140.full},

doi = {10.1117/12.2582140},

year  = {2021},

date = {2021-02-15},

booktitle = {SPIE Medical Imaging},

volume = {11595},

pages = {115950W},

publisher = {International Society for Optics and Photonics},

keywords = {CBCT, Machine Learning/Deep Learning, Motion Compensation},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Capostagno2020,

title = {Image-based deformable motion compensation in cone-beam CT: translation to clinical studies in interventional body radiology},

author = {Sarah Capostagno and Alejandro Sisniega and J. Webster Stayman and Tina Ehtiati and Clifford Weiss and Jeffrey H. Siewerdsen},

url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11315/0000/Image-based-deformable-motion-compensation-in-cone-beam-CT/10.1117/12.2549998.full},

doi = {10.1117/12.2549998},

year  = {2020},

date = {2020-03-16},

booktitle = {SPIE Medical Imaging},

volume = {11315},

pages = {113150B},

publisher = {International Society for Optics and Photonics},

keywords = {CBCT, Image Guided Surgery, Motion Compensation},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Sisniega2018b,

title = {Multi-Motion Compensation for High-Quality Cone-Beam CT of the Head},

author = {Alejandro Sisniega and Wojciech Zbijewski and Pengwei Wu and J. Webster Stayman and Nafi Aygun and R. Stevens and Xiaohui Wang and David H. Foos and Jeffrey H. Siewerdsen },

year  = {2018},

date = {2018-05-20},

booktitle = {International Conference on Image Formation in X-Ray Computed Tomography},

pages = {73-77},

keywords = {Artifact Correction, Head/Neck, Motion Compensation},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Sisniega2016,

title = {Image-based motion compensation for high-resolution extremities cone-beam CT},

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

editor = {Despina Kontos and Thomas G. Flohr and Joseph Y. Lo},

url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4918632/},

doi = {10.1117/12.2217243},

year  = {2016},

date = {2016-03-01},

booktitle = {SPIE Medical Imaging},

pages = {97830K},

publisher = {International Society for Optics and Photonics},

keywords = {Extremities, High-Resolution CT, Motion Compensation},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Sisniega2016a,

title = {Motion Estimation Using a Penalized Image Sharpness Criterion for Resolution Recovery in Extremities Cone-Beam CT},

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

url = {https://aiai.jhu.edu/papers/CT2016_Sisniega.pdf},

year  = {2016},

date = {2016-01-01},

booktitle = {4th International Conference on Image Formation in X-Ray Computed Tomography},

pages = {549--552},

keywords = {Artifact Correction, CBCT, Extremities, High-Resolution CT, Motion Compensation},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Jacobson2008,

title = {Compensating for head motion in slowly-rotating cone beam CT systems with optimization transfer based motion estimation},

author = {Matthew W. Jacobson and J. Webster Stayman },

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4774416},

doi = {10.1109/NSSMIC.2008.4774416},

issn = {1082-3654},

year  = {2008},

date = {2008-10-01},

booktitle = {2008 IEEE Nuclear Science Symposium Conference Record},

pages = {5240--5245},

publisher = {IEEE},

abstract = {We present an algorithm that estimates the changing pose of a rigidly moving subject, based on tomographic projections of fiducial markers. The pose estimates can then be used as input data to motion-compensated image reconstruction methods. The proposed algorithm is in the family of so-called optimization transfer algorithms, which have been applied more frequently to tomographic image reconstruction (e.g., the ML-EM algorithm for PET). The algorithm is particularly relevant to the class of slowly-rotating, point-of-care cone beam CT systems, which have recently become prominent in otolaryngological and dental clinics for head and neck scanning. These systems are more compact and inexpensive than traditional CT systems, but because of their slower gantry rotation, are more susceptible to patient head motion over the course of the scan. A virtue of our algorithm is that it does not require a priori knowledge of the marker geometry. The relative positions of the markers are co-estimated together with their 6 degree of freedom position/orientation in each projection view. This means that the marker configuration can be deformably adjusted to fit different patients, giving considerably more flexibility in the design of the marker-to-head attachment gear than with conventional fiducial-based approaches. Our algorithm is also both fast and accurate. In a highly sub-optimal MATLAB implementation, we typically achieve motion estimates yielding sub-millimeter positioning error in 15–30 seconds. We also present motion-compensated reconstructions from real CT acquisitions as evidence of motion-estimation performance.},

keywords = {Artifact Correction, CBCT, Motion Compensation},

pubstate = {published},

tppubtype = {inproceedings}

}