Radiation and Cancer Physics
SS 33 - Physics 10- Machine Learning for Planning and Segmentation
9/18/2019
11:15 AM - 12:30 PM
Location: Room W185
Session Type: Scientific
1.25 AMA PRA Category 1 Credits™
1.25 CAMPEP Credits
Presentations:
11:15 AM - 11:25 AM
A Generative Adversarial Network (GAN)-based Approach for Automatic Fiducial Marker Detection in MR Radiotherapy Simulation Images
Presenter: – UCLA
Presentation No : 189
11:25 AM - 11:35 AM
Abdominal Multi-Organ Auto-Segmentation with 3D-Patch Based Deep Convolutional Neural Network
Presenter:
Presentation No : 190
11:35 AM - 11:45 AM
Shape Constrained Fully Convolutional DenseNet with Adversarial Training for Multi-organ Segmentation on Head and Neck Low Field MR Images
Presenter: – UCLA Radiation Oncology
Presentation No : 191
11:45 AM - 11:55 AM
A Human Behavior-Driven Deep-Learning Approach for Automatic Sigmoid Segmentation
Presenter:
Presentation No : 192
11:55 AM - 12:05 PM
Implementation of Machine Learning-Based Treatment Planning Tool for Whole Breast Radiotherapy Using Irregular Surface Compensator Technique
Presenter: – Duke University Medical Center
Presentation No : 193
12:05 PM - 12:15 PM
A Subjective Bayesian Network Approach to Develop a Human-in-the-Loop Decision Support System for Personalized Adaptive Radiotherapy in Non-Small-Cell Lung Cancer (NSCLC)
Presenter: – University of Michigan
Presentation No : 194
12:15 PM - 12:25 PM
An Image-Based Framework for Individualizing Radiotherapy Dose
Presenter: – Cleveland Clinic Taussig Cancer Institute
Presentation No : 195