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2021 AAPM Virtual 63rd Annual Meeting - Session: Science Council Session: Innovative Technologies to Advance Diagnosis and Treatment Q & A


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Q & A




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All videos in this session:
An Imaging Based Biological Framework for Personalizing Radiation Therapy of Lung Cancer Using Interpretable Bayesian Networks and NTCP-Based Treatment Planning - Ali Ajdari Harvard Medical School & Massachusetts General Hospital
BEST IN PHYSICS (MULTI-DISCIPLINARY): Focused KV X-Rays for Radiotherapy and Imaging of Small Targets - Wu Liu, PhD Stanford University
Biologically Guided Deep Learning for Post-Radiation PET Image Outcome Prediction: A Feasibility Study of Oropharyngeal Cancer Application - Chunhao Wang, PhD Duke University Medical Center
Computing Dose to Circulating Blood Cells Using Whole-Body Blood Flow Simulations - Jungwook Shin Massachusetts General Hospital
Deep Learning-Based Framework for the Assessment of Radiation Dermatitis in Nasopharyngeal Carcinoma (NPC) Patients - Ruiyan Ni The Hong Kong Polytechnic University
Patient-Specific Deep Learning-Based Self-High-Resolution for MR Imaging - Yang Lei Emory Univ
Spatiotemporal Dose Characterization of An Electron FLASH Beam From a LINAC Using Radioluminescence and Cherenkov Imaging - Mahbubur Rahman Dartmouth College
Thermoacoustic Range Verification During Pencil Beam Delivery of a Clinical Plan to An Abdominal Imaging Phantom  - Sarah Patch UW-Milwaukee
Thoracic 4D Cone-Beam CT Registration Incorporating a Fan-Beam CT-Derived Feasible Motion Descriptor - Yudi Sang UCLA
Toward Magnetic Resonance Fingerprinting for Low-Field MR-Guided Radiation Therapy - Nikolai Mickevicius University of Wisconsin
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