DISCLAIMER:
Entry of taxonomy/keywords during proffered abstract submission was optional.
Not all abstracts will appear in search results.
Keywords: registration
| MO-B-BRC-2 | Comprehensive Evaluation of a Real-Time 3D MR Imaging Technique Using a Deformation-Driven Deep Convolutional Neural Network (KS-RegNet) H Shao1*, T Li2, M Dohopolski1, J Wang1, J Cai2, J Tan1, K Wang1, Y Zhang1, (1) The University of Texas Southwestern Medical Center, Dallas, TX, (2) The Hong Kong Polytechnic University, Hong Kong, HK |
| MO-E115-IePD-F2-2 | On the Utilization of a Pseudo-Inverse Consistency Metric to Evaluate Deformable Dose Accumulation Error for MRI-Guide Adaptive Radiotherapy H Zhong*, J Garcia-Alvarez, K Kainz, X Li, Medical College of Wisconsin, Milwaukee, WI |
| MO-FG-BRB-10 | An Integrated Machine Learning and Biomechanical Modeling Guided Deformable Image Registration Framework for Consistent Parenchymal Tissue Tracking in Lung CT Scans B Stiehl*, M Lauria, L Naumann, D O'Connell, P Boyle, I Barjaktarevic, D Low, A Santhanam, UCLA, Los Angeles, CA |
| MO-H345-IePD-F1-2 | A Patient-Specific Approach for Estimating the Voxel-Level Uncertainty Distribution of Deformable Image Registration in Adaptive Radiotherapy S Meyer*, S Alam, L Kuo, Y Hu, L Cervino, P Zhang, Memorial Sloan Kettering Cancer Center, New York, NY |
| MO-H345-IePD-F1-3 | A Novel Edge Gradient Distance Metric for Automated Evaluation of Deformable Image Registration Quality Y Xu1*, J Ford1, J Williamson3, N Dogan1, (1) University of Miami, Miami, FL, (2) Washington University, Richmond, VA |
| MO-H345-IePD-F1-5 | A Practical Guide to Radiotherapy Image Registration Software Commissioning with TG-132 Common Dataset Y Natsuaki, M Fan, T McDaniels, R Shaw, P Sansourekidou*, University of New Mexico, Albuquerque, NM |
| MO-H345-IePD-F2-4 | Deep Learning-Based Simultaneous Multi-Phase Deformable Image Registration of Sparse 4D-CBCT I Herzig1*, P Paysan2, S Scheib2, F-P Schilling3, J Montoya3, M Amirian3, T Stadelmann3, P Eggenberger1, R Fuechslin1, L Lichtensteiger1, (1) Zurich University of Applied Sciences ZHAW, Institute for Applied Mathematics and Physics IAMP, Winterthur, CH (2) Varian Medical Systems Imaging Laboratory, Daettwil AG, CH (3) Zurich University of Applied Sciences ZHAW, Centre for Artificial Intelligence CAI, Winterthur, CH |
| PO-GePV-I-10 | Development of a Deformable Image Registration Technique for Abdominal Cone-Beam CT Using Deep Learning with Generative Adversarial Network Y Zhang1,2, Y Liu1,2, l tie1,2, H Gong2, W Zhao1, G Zhang1, S Xu3*, (1) Beihang University, School of Physics, Beijing, China. (2) The First Medical Center of PLA General Hospital, Department of Radiation Oncology, Beijing, China.(3) National Cancer Center/Cancer Hospital- Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Radiation Oncology, Beijing, China |
| PO-GePV-M-46 | Region Specific Optimization (RSO)-Based Deep Interactive Registration T Bai1*, M Lin1, X Liang1, B Wang1,2, M Dohopolski1, B Cai1, D Nguyen1, S Jiang1, (1) The University of Texas Southwestern Medical Ctr, Dallas, TX, (2) Southern Methodist University, Dallas, TX |
| PO-GePV-M-119 | DVH Distortion in Deformably Propagated Dose Grids - a Practical Challenge for Adaptive Radiotherapy J Kipritidis1*, A Quinn1, T Morgas2, S Kuckertz3, N Papenberg3, S Heldmann3, T Coradi2, F Franco2, J Kieselmann2, C Huang2, J Booth1, (1) Northern Sydney Cancer Centre, Sydney, NSW, AU, (2) Varian Medical Systems, Palo Alto, CA, (3) Fraunhofer MEVIS, Lubeck, DE |
| PO-GePV-M-174 | Evaluation of Deformation Image Registration Algorithms Based On Deformation Vector Field for Radiotherapy E Li1,2, Z Zhong1,2, Y An1,2, S Huang1, W Zheng1,3, J Lian1,4, X Yang1*, (1) Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong province, 510060, China,(2) Guangzhou Xinhua College, Guangzhou, Guangdong, 510520, China,(3) Department of Radiation Oncology, Southern Theater Air Force Hospital of the People's Liberation Army, Guangzhou, Guangdong province, 510050, China,(4) Department of Radiation Oncology, The First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, Guangdong province, 510405, China |
| PO-GePV-M-177 | Determination of the Elastostatic Force Exerted in the Lungs During Breathing From Image Registration S Bhandari*,A Bain, J Jung, , East Carolina Univ, Greenville, NC |
| PO-GePV-M-180 | Multimodality Image Registration and Fusion Using Deep Learning for Radiotherapy Planning A Ratke*1, E Darsht1, C Baeumer2, B Spaan1, K Kroeninger1, (1) TU Dortmund University, Dortmund, DE, (2) West German Proton Therapy Centre Essen, Essen, DE |
| PO-GePV-M-181 | MR-CT Image Registration by Using Unsupervised Deep Learning Model M Tavakoli1*, S Abbasi2, H Hamid Reza Boveiri3, M Mosleh-Shirazi4, A Mehdizadeh5, (1) University of Pittsburgh School of Medicine and UPMC Hillman Cancer Center, Pittsburgh, PA, USA, PA, (2) Shiraz University of Medical Sciences, Shiraz, IR, (3) Sama College, Iau, Shoushtar Branch, (4) Shiraz University of Medical Sciences, Shiraz, IR, (5) Shiraz University Of Medical Sciences, |
| PO-GePV-M-186 | Quantitative Evaluation and Feasibility Study of Using AI Denoising Technique to Minimize Image Dose of 2.5MV Beam H Kuo1*, S Lim1, S Lin2, J Sillanpaa1, L Cervino1, (1) Memorial Sloan Kettering Cancer Center, New York, NY (2) Norwalk Hospital, Norwalk, CT |
| PO-GePV-M-193 | Investigation of Registration Uncertainty Caused by DRR Resolution for Motion Tracking in Spinal Treatments W Cai, X He, F Li, P Zhang, L Cervino, J Moran, T Li*, X Li, Memorial Sloan Kettering Cancer Center, New York, NY |
| PO-GePV-M-266 | Quantifying Setup Uncertainties in Treating Intramuscular Metastases with Image-Guided Radiation Therapy S Prajapati*, Z Yu, Y Zhao, T Lim, H Wang, X Wang, B Lee, P Castillo, A Sobremonte, A Farooqi, D Mitra, R Kudchadker, C Tang, J Yang, UT MD Anderson Cancer Center, Houston, TX |
| PO-GePV-M-329 | Expanding Access to SGRT-Based Patient Alignment Using Mixed Reality Visualization P Johnson1,2*, S Lampotang2, D Lizdas2, W Johnson2, A Jackson2, (1) University of Florida Health Proton Therapy Institute, Jacksonville, FL, (2) University Of Florida, Gainesville, FL |
| PO-GePV-T-91 | Study On Correction Accuracy of Couch Sag in CT-Linac L Yu, B Yang, X Liu, T Pang, J Qiu*, Peking Union Medical College Hospital, Beijing, 11CN, |
| SU-F-BRB-1 | Adversarial Attacks On a Regression Based Deep Registration Network F Li*, W Cai, X He, J Moran, L Cervino, T Li, X Li, Memorial Sloan Kettering Cancer Center, New York, NY |
| SU-F-BRB-8 | Synthesizing Continuous 4D Respiratory Motion Using a Conditional Registration Network Y Sang*, D Ruan, University of California, Los Angeles, CA |
| SU-H300-IePD-F8-3 | Application of Lambda: Subvoxel Image Similarity in Complex Images P Boyle*, M Lauria, B Stiehl, L Naumann, A Santhanam, D Low, UCLA, Los Angeles, CA |
| SU-H400-IePD-F8-5 | Automated Deformable Registration Using Patch-Based ViT-Morph for MR-Guided Adaptive Radiotherapy Y Zhao*, X Chen, C Yu, L Court, B McDonald, T Pan, H Wang, X Wang, J Phan, J Yang, UT MD Anderson Cancer Center, Houston, TX |
| TH-B-207-3 | Phase-Resolved Lung Ventilation Imaging Method Based On Four-Dimensional Computed Tomography Y Huang*, G Ren, H Xiao, Y Li, Z Chen, X Teng, Z Ma, J Cai, The Hong Kong Polytechnic University, Hong Kong |
| TH-E-BRC-3 | Longitudinal Unsupervised Deformable Image Registration Network for Adaptive Radiotherapy D Lee*, Y Hu, S Alam, J Jiang, L Cervino, P Zhang, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY |
| TH-E-BRC-4 | MRIGRT - 4D Motion Modeling and Real-Time Online 3D Motion Tracking y zhang1, X Wu1*, H Gach1, J Ginn2, D Yang2, (1) Washington University, Saint Louis, MO, (2) Duke University, Chapel Hill, NC |
| TH-F-201-5 | Real-Time Registration for Fast KV-Switching 2D Dual-Energy Angiography E Nikolau*, M Wagner, P Laeseke, M Speidel, University of Wisconsin - Madison, Madison, WI |
| TH-F-BRC-5 | MUsculo-Skeleton-Aware Deep Learning-Based Deformable Registration for Head-And-Neck CT with a Relaxed Rigidity Constraint On Bony Structures H Liu1,2*, E McKenzie3, Q Xu1,2, D Ruan1,2, K Sheng1,2, (1) UCLA, Los Angeles, CA, (2) UCLA School of Medicine, Los Angeles, CA, (3) Cedars-Sinai Medical Center, Los Angeles, CA |
| TU-D1030-IePD-F1-4 | Evaluation of Different Holographic Visualization Techniques for Surface-Guided Patient Alignment Using Mixed Reality (MixR) and the Microsoft Hololens 2 A Jackson1*, P Johnson2, E Feldman2, A Martin-gomez3, (1) Mayo Clinic, Jacksonville, FL, (2) University of Florida Health Proton Therapy Institute, Jacksonville, FL, (3) Johns Hopkins University Whiting School Of Engineering, Baltimore, MD, |
| TU-I345-IePD-F5-6 | Test-Time Adaptation for Deformable Image Registration Y Sang*, M McNitt-Gray, Y Yang, M Cao, D Low, D Ruan, University of California, Los Angeles, CA |
| WE-C1000-IePD-F2-1 | 3D Ultrasound to 3D MR Image Registration for Motion Management in the Liver Using Novel MR-Compatible Ultrasound Probe S Jupitz*, B Bednarz, University of Wisconsin, Madison, WI |
| WE-C1000-IePD-F6-3 | Investigating the Feasibility of CT Ventilation Imaging On Fast, Low-Dose 4DCBCT to Enable Daily Adaptive Lung Function Sparing H Byrne1*, O Dillon1, S Blake1, J Kipritidis2, R O'Brien1, P Keall1, (1) ACRF Image X Institute, The University of Sydney, Sydney, AU (2) Northern Sydney Cancer Centre, Royal North Shore, Sydney, AU |
| WE-C930-IePD-F5-1 | Real-Time Liver Tumor Localization Via a Single X-Ray Projection Using Graph Neural Network and Deep Learning-Based Biomechanical Modeling (MeshRegNet-Bio) H Shao*, T Bai, J Wang, J Chun, J Park, S Jiang, Y Zhang, The University of Texas Southwestern Medical Ctr, Dallas, TX |