Jeffrey Siewerdsen
Affiliations: | Biomedical Engineering | Johns Hopkins University, Baltimore, MD |
Area:
Biomedical Engineering, RadiologyGoogle:
"Jeffrey Siewerdsen"Children
Sign in to add trainee| Yifu Ding | research assistant | 2010-2012 | Johns Hopkins |
| Daniel J. Mirota | grad student | 2012 | Johns Hopkins |
| Sajendra Nithiananthan | grad student | 2013 | Johns Hopkins |
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Publications
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| Huang Y, Zhang X, Hu Y, et al. (2024) Deformable registration of preoperative MR and intraoperative long-length tomosynthesis images for guidance of spine surgery via image synthesis. Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society. 114: 102365 |
| Johnston A, Mahesh M, Uneri A, et al. (2024) Objective image quality assurance in cone-beam CT: Test methods, analysis, and workflow in longitudinal studies. Medical Physics |
| Stewart HL, Siewerdsen JH, Selberg KT, et al. (2023) Cone-beam computed tomography produces images of numerically comparable diagnostic quality for bone and inferior quality for soft tissues compared with fan-beam computed tomography in cadaveric equine metacarpophalangeal joints. Veterinary Radiology & Ultrasound : the Official Journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association. 64: 1033-1036 |
| Lu A, Huang H, Hu Y, et al. (2023) Deformable Motion Compensation for Intraprocedural Vascular Cone-beam CT with Sequential Projection Domain Targeting and Vessel-Enhancing Autofocus. Proceedings of Spie--the International Society For Optical Engineering. 12466 |
| Brock KK, Chen SR, Sheth RA, et al. (2023) Imaging in Interventional Radiology: 2043 and Beyond. Radiology. 308: e230146 |
| Wu P, Tersol A, Clackdoyle R, et al. (2023) Cone-beam CT sampling incompleteness: analytical and empirical studies of emerging systems and source-detector orbits. Journal of Medical Imaging (Bellingham, Wash.). 10: 033503 |
| Zhang X, Sisniega A, Zbijewski WB, et al. (2023) Combining physics-based models with deep learning image synthesis and uncertainty in intraoperative cone-beam CT of the brain. Medical Physics |
| Ding AS, Lu A, Li Z, et al. (2023) A Self-Configuring Deep Learning Network for Segmentation of Temporal Bone Anatomy in Cone-Beam CT Imaging. Otolaryngology--Head and Neck Surgery : Official Journal of American Academy of Otolaryngology-Head and Neck Surgery |
| Liu SZ, Herbst M, Weber T, et al. (2022) Dual-Energy Cone-Beam CT with Three-Material Decomposition for Bone Marrow Edema Imaging. Proceedings of Spie--the International Society For Optical Engineering. 12304 |
| Ma YQ, Gang GJ, Reynolds T, et al. (2022) Practical workflow for arbitrary non-circular orbits for CT with clinical robotic C-arms. Proceedings of Spie--the International Society For Optical Engineering. 12304 |