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Taxonomy: IM/TH- MRI in Radiation Therapy: MRI/Linear accelerator combined- IGRT and tracking
| SU-L-SAN2-6 | Motion Prediction Confidence Estimation for MRI-Guided Radiotherapy J Ginn*, D Low , J Lamb , D Ruan , University of California, Los Angeles, Los Angeles, CA |
| SU-L-SAN2-7 | On the Development of Real-Time Motion Tracking Using 2D-To-3D MRI Registration for MR-Linac T Keiper1*, A Tai2 , L Wang3 , X Chen4 , E Paulson5 , F Lathuiliere6 , D Cooper7 , M Lachaine8 , X Li9 , (1) Medical College of Wisconsin, Milwaukee, WI, (2) Medical College of Wisconsin, Milwaukee, WI, (3) Medical College of Wisconsin, Milwaukee, WI, (4) Medical College of Wisconsin, Milwaukee, WI, (5) Medical College of Wisconsin, Milwaukee, WI, (6) Elekta, Montreal, QC,(7) Elekta, Montreal, QC,(8) Elekta, Montreal, QC, (9) Medical College of Wisconsin, Milwaukee, WI |
| TH-A-225BCD-4 | Adaptive Boosting and Multi-Layer Perceptron Neural Network (ADMLP-NN) for Predicting Real-Time 3D Deformation Field Maps (DFM) for 4D Target Tracking J Pham1*, W Harris2 , W Sun3 , Z Yang4 , F Yin1 , L Ren1 , (1) Duke University Medical Center, Durham, NC, (2) University of Pennsylvania, Philadelphia, PA, (4) Shandong University, Qingdao, China, (5) UT Southwestern Medical Center, Dallas, TX |
| TH-BC-303-7 | A Potential Approach of Real-Time Motion Tracking of MR-Guided-Radiotherapy Using Ultra-Fast Volumetric 4D-MRI Generated VOI Positional Probability Distribution O Wong*, J Yuan , Y Zhou , S Yu , K Cheung , Hong Kong Sanatorium & HospitalHong Kong |
| TH-BC-303-8 | Image Regression Motion Prediction for MRI-Guided Radiotherapy J Ginn*, D Ruan , D Low , J Lamb , University of California, Los Angeles, Los Angeles, CA |
| TH-BC-303-9 | A 2.5D+1 Model for Improved Targeting Accuracy in MR Linac J Wu*, G Yan , S Samant , University of Florida, Gainesville, FL |
| TU-K430-CAMPUS-F2-5 | PTV Reduction with Time-Weighted Mid-Position Images for 4D-MRI Guided Online Adaptive Radiation Therapy A Tai*, X Chen , N Mickevicius , E Paulson , E Ahunbay , X Li , Medical College of Wisconsin, Milwaukee, WI |
| TU-L-225BCD-5 | MRI Super-Resolution Reconstruction for MRI-Guided Adaptive Radiotherapy Using Cascaded Deep Learning: In the Presence of Limited Training Data and Unknown Translation Model J Chun1,3*, H Gach1,2 , S Olberg1 , T Mazur1 , O Green1 , T Kim1 , H Kim1 , J Kim3 , S Mutic1 , J Park1 , (1) Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, (2) Departments of Radiology and Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, (3) Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, South Korea |
