| Sunday
4:30 PM | SU-F-TRACK 6-1 : Automatic Stent Recognition Using Deep Neural Network for Quantitative Intra-Fractional Motion Monitoring in Pancreatic Cancer Radiotherapy
X. He*, W. Cai, F. Li, P. Zhang, L. Cervino, T. Li, X. Li |
| Sunday
4:37 PM | SU-F-TRACK 6-2 : Dual-Energy Real-Time Stereoscopic X-Ray Image Guidance for Markerless Lung Tumor Tracking
C. Peacock, M. Sattarivand* |
| Sunday
4:44 PM | SU-F-TRACK 6-3 : Implementation of High-Quality Motion-Compensated Simultaneous Algebraic Reconstruction Technique (mc-SART) Cone-Beam CT (CBCT) Imaging Using the 5D Model in a Prospective Patient Study
K. Singhrao*, D. O'Connell, J. Fu, M. Lauria, B. Stiehl, A. Raldow, J. Hegde, A. Lee, A. Santhanam, D. Low, J. Lewis |
| Sunday
4:51 PM | SU-F-TRACK 6-4 : One-Second Into the Future: A Deep Learning Method to Predict 3D Lung Cancer Target Motion to Account for Adaptation Latency
Q. Hoang, J. Booth, V. Caillet, P. Keall, D. Nguyen* |
| Sunday
4:58 PM | SU-F-TRACK 6-5 : BEST IN PHYSICS (MULTI-DISCIPLINARY): Real-Time Dose-Optimized Multi-Target MLC Tracking for Locally Advanced Prostate Cancer
E. Hewson*, D. Nguyen, J. Booth, P. Keall, L. Mejnertsen |
| Sunday
5:05 PM | SU-F-TRACK 6-6 : Synthesizing Real-Time In-Treatment 4D Images Based On Optical Surface Signals and Pre-Treatment Images: A Proof-Of-Concept Study
Y. Huang*, Y. Zhang |
| Sunday
5:12 PM | SU-F-TRACK 6-7 : Evaluating the Clinical Impact and Accuracy of Real-Time KV Imaging in Liver SBRT
A. Santoso*, Y. Vinogradskiy, T. Robin, K. Goodman, T. Schefter, M. Miften, B. Jones |
