SS 17 - Phys 4: Machine Learning

Moderator(s)

• 

  Jing Wang, PhD

  University of Texas Southwestern Medical Center
  Dallas, Texas, United States
• EM

  Elizabeth McKenzie, PhD, MS

  Cedars Sinai Medical Center
  Los Angeles, CA

Presentations:

• 10:45 AM – 10:55 AM ET

  A Deep Learning-Driven Framework for Large Language Model-Assisted Automatic Target Volume Localization and Delineation for Enhancing Spinal Metastases Stereotactic Body Radiotherapy Workflow
  

  Presenter: Zi Yang, PhD – Stanford University
• 10:55 AM – 11:05 AM ET

  Identifying Candidates for Postoperative Radiotherapy in Patients with Non-Small Lung Cancer: Multicenter Deep Learning Model Development and Prospective Validation
  

  Presenter: Zeliang Ma, MD – Mayo Clinic Rochester
• 11:05 AM – 11:15 AM ET

  SAM-ART: An Efficient Segmentation Method with a Large Vision Model for MRI-Guided Adaptive Radiotherapy
  

  Presenter: Bining Yang, PhD – National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy
• 11:15 AM – 11:25 AM ET

  Deep Learning-Based Quick MLC Sequencing for MRI-Guided Online Adaptive Radiotherapy
  

  Presenter: Ahmet Ahunbay, BS – Medical College of Wisconsin
• 11:25 AM – 11:35 AM ET

  A Reinforcement Learning Approach to Automate Breast Radiation Therapy Treatment Planning Using Electronic Compensation (ECOMP)
  

  Presenter: Dongrong Yang, MS, BS – Duke University Medical Center
• 11:35 AM – 11:45 AM ET

  Automated Treatment Planning with Deep Reinforcement Learning for Head-and-Neck Cancer Intensity Modulated Radiation Therapy
  

  Presenter: Dongrong Yang, MS, BS – Duke University Medical Center
• 11:45 AM – 11:55 AM ET

  Gross Tumor Volume Auto Delineation Based on a Novel Multimodal Adaptive Segmentation Model in Multicenter Nasopharyngeal Carcinoma Radiotherapy
  

  Presenter: Hongfei Sun, PhD