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Taxonomy: IM/TH- Cone Beam CT: Machine learning, computer vision

PO-GePV-M-121Deep-Learning Based Auto-Classification of Anatomical Regions for IGRT Applications: Implementation and Explainability
J Cruz Bastida*, S Li, E Pearson, H Al-Hallaq, The University of Chicago, Chicago, IL
SU-B-TRACK 6-4Managing Tumor Changes During Fractionated Radiotherapy: Evaluation On a Deep-Learning-Based Predictive Model and a Re-Planning Strategy
R Li1*, A Roy2, N Kirby1, N Bice1, S Sivabhaskar1, M Fakhreddine1, N Papanikolaou1(1) UT Health San Antonio MD Anderson Cancer Center, San Antonio, Texas, (2) The University of Texas at San Antonio, San Antonio, Texas
SU-D-TRACK 4-2Automated Predictive Models for Lung ART
J Kavanaugh1*, G Hugo1, Z Ji1, J Fontenot4, (1) Washington University School of Medicine, St. Louis, MO, (2) Mary Bird Perkins Cancer Center, Baton Rouge, LA
TU-B-TRACK 6-1Dose Tracking Using CBCT During Head and Neck Proton PBS Radiotherapy: A Feasibility Study
C Liu1,3*, G Janssens2, L Hong2, X Liang1, Y Zhang1, (1) University of Florida Proton Therapy Institute, Jacksonville, FL, (2) Ion Beam Applications SA, Louvain-la-neuve, BE, (3) University of Science and Technology of China, Hefei, ,CN,
TU-C-TRACK 3-1A Deep Learning Technique for Projection Interpolation in CBCT Reconstruction
K Lu1*, Z Zhang1, L Ren2, F Yin2, (1) Duke University, Durham, NC, (2) Duke University Medical Center, Durham, NC
TU-D-TRACK 3-3Multi-Resolution Residual Deep Neural Network for Generating Synthetic CT Images with High HU Accuracy and Structural Fidelity
W WU1*,J Qu2, J Cai3, R Yang1, (1) Peking University Third Hospital, Beijing, China (2) Capital Medical University, Beijing, China (3) The Hong Kong Polytechnic University, Hong Kong, China