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Keywords: motion artifacts
| PO-GePV-M-98 | An Improved 4DCT Reconstruction Algorithm for Patients with Irregular Breathing A Harnage1*, C Ramsey1,2, M Ratner1, J Bowling2, I Pfeiffer2, (1) University of Tennessee, Knoxville, TN, (2) Thompson Cancer Survival Center, Knoxville, TN |
| PO-GePV-M-162 | Variation in Relative Left and Right Diaphragm Positions Across Imaging Sessions Using CT Simulation and Cone-Beam CT Images M Lauria1*, K Singhrao2, J Lewis3, D O'Connell1, W Lin4, A Santhanam1, L Naumann1, B Stiehl1, P Boyle1, P Lee5, D Low1, (1) UCLA, Los Angeles, CA, (2) UCSF, San Francisco, CA, (3) Cedars-Sinai Medical Center, Pacific Palisades, CA, (4) Pepperdine University, Malibu, CA, (5) MD Anderson Cancer Center, Houston, TX |
| PO-GePV-T-4 | Simulation of 4DCT Phase-Based Measurement Errors in Tumor Size and Motion L Naumann*, R Savjani, M Lauria, B Stiehl, P Boyle, A Santhanam, D Low, UCLA, Los Angeles, CA |
| PO-GePV-T-278 | Free Breathing Or Breath Hold for Pancreas Treatment Planning? T Lin*, C Ma, Fox Chase Cancer Center, 333 Cottman Ave., Philadelphia, PA 19111, USA |
| SU-I400-BReP-F2-4 | CBCT Forecasting - A Convolution-LSTM Based Machine Learning Framework for Predicting “ahead-Of-Time” Patient Anatomy, Dose to Be Delivered, and Dose Trend in Head and Neck Radiotherapy A Santhanam1*, B Stiehl1, M Lauria1, R Savjani1, S Gros2,D Low1, (1) University of California, Los Angeles, Los Angeles, CA, (2) Loyola University Chicago, Chicago IL |
| TH-B-202-5 | PET Quantification in 50% Counts DDG-PET/CT: Noise, Motion Correction, And Misregistration Effects A Thomas1*, J Meier2, O Mawlawi1, P Sun1, T Pan1, (1) UT MD Anderson Cancer Center, Houston, TX, (2) University of Wisconsin Medical Radiation Research Center, Madison, WI |
| TH-D-201-3 | Evaluation of Geometric Accuracy and Iodine Quantification of High-Pitch Multi-Energy Cardiac Imaging with Dual-Source Photon-Counting Detector CT Z Ahmed*, D Campeau, H Gong, K Rajendran, P Rajiah, C McCollough, S Leng, Mayo Clinic, Rochester, MN |
| TH-E-201-3 | BEST IN PHYSICS (IMAGING): Deep Learning-Based Motion Compensation for 4D-CBCT Reconstruction Z Zhang1*, J Liu2, D Yang3, U Kamilov2, G Hugo1, (1) Washington University School of Medicine in St. Louis, St. Louis, MO, (2) Washington University in St. Louis, St. Louis, MO, (3) Duke University, Chapel Hill, NC |
| WE-A-201-6 | BEST IN PHYSICS (IMAGING): Respiratory Motion Detection and Reconstruction Using CAPTURE and Deep Learning Phase2Phase Network for a 0.35 T MRI-LINAC System S Chen1*, C Eldeniz2, T Fraum3, D Ludwig4, W Gan5, U Kamilov6, D Yang7, Gach8, H An9, (1) Washington University in St. Louis, Saint Louis, MO, (2) Washington University in St. Louis, Saint Louis, MO, (3) Washington University in St. Louis, Saint Louis, MO, (4) Washington University in St. Louis, Saint Louis, MO, (5) Washington University in St. Louis, Saint Louis, MO, (6) Washington University in St. Louis, St. Louis, MO, (7) Duke University, Chapel Hill, NC, (8) Washington University in St Louis, Saint Louis, MO, (9) Washington University in St. Louis, Saint Louis, MO |
| WE-C1000-IePD-F1-5 | On the Experimental Test of a Blurry Image Decomposition Algorithm for Correction of PET Motion Artifacts for Stereotactic Body Radiotherapy H Zhong*, Y Lu, N Morrow, E Gore, X Li, Y Liu, Medical College of Wisconsin, Milwaukee, WI |