Click here to

Expand All | Collapse All

Objectives

  1. Provide an overview of AI application in radiation oncology and medical imaging
  2. Review biomedical data science and infrastructure requirements for AI
  3. Review latest development of AI algorithms and solutions
  4. Discuss impact of AI on risk management, ethics, and fair healthcare

Program Outline

Thursday, April 28 (All times PDT)
8:30 AM – 8:40 AM Opening Remarks Xuejun Gu
Issam El Naqa
Lei Xing
Yi Wang
8:40 AM – 9:20 AM Medical Imaging in the Era of Artificial Intelligence Curtis Langlotz
9:20 AM – 10:00 AM Challenges in AI and its Practical Application Ceferino Obcemea
10:00 AM – 10:15 AM Open Q&A with Speakers Curtis Langlotz
Ceferino Obcemea
Break (10:15 AM – 10:30 AM)
10:30 AM – 11:00 AM Medical Physics and Radiation Oncology in the Age of AI Lei Xing
11:00 AM – 11:30 AM Explainable AI in Biomedicine Su-In Lee
11:30 AM – 12:00 PM AI Infrastructure Needs for Biomedical Research David Jaffray
12:00 PM – 12:30 PM Open Q&A with Speakers Lei Xing
Su-In Lee
David Jaffray
Break (12:30 PM – 1:30 PM)
1:30 PM – 2:00 PM Recent Advances in Deep Learning and Big Data Matei Zaharia
2:00 PM – 2:30 PM The Role of Data in Medical Imaging AI Akshay Chaudhari
2:30 PM – 2:45 PM Open Q&A with Speakers Matei Zaharia
Aksay Chaudhari
Break (2:45 PM – 3:00 PM)
3:00 PM – 3:30 PM AI in MRI-guided Radiation Therapy James Dempsey
3:30 PM – 4:00 PM Clinical Perspective of AI: Opportunities and Challenges C. David Fuller
4:00 PM – 4:30 PM Panel Discussion: Clinical Aspects and Commercialization of AI James Dempsey
C. David Fuller
Friday, April 29 (All times PDT)
8:30 AM – 9:00 AM Data-driven Image Reconstruction GuangHong Chen
9:00 AM – 9:30 AM Clinical Implementation of Deep Learning for RT Auto Segmentation Yi Wang
9:30 AM – 10:00 AM Deep Learning for RT Treatment Planning Xun Jia
10:00 AM – 10:15 AM Open Q&A with Speakers GuangHong Chen
Yi Wang
Xun Jia
Break (10:15 AM – 10:30 AM)
10:30 AM – 11:00 AM Deep Learning for IGRT Xuejun Gu
11:00 AM – 11:30 AM Outcome and AI Modeling Issam El Naqa
11:30 AM – 12:00 PM Panel Discussion: New Frontiers of Medical AI – Innovation & Creativity GuangHong Chen
Xuejun Gu
Issam El Naqa
Keyvan Farahani
Lei Xing
Break (12:00 PM – 1:15 PM)
1:15 PM – 2:45 PM
Student & Trainee Showcase
Adaptive Sparse-View CT Deep Reconstruction by Residual Signal Learning - Bowen Song, Stanford University
Physics-driven Spatial-Temporal Neural Representation Network for Low-Dose 4DCT Image Reconstruction - Siqi Ye, Stanford University
Deep Learning-based Rapid Delineation of Organs at Risk for Patient-Specific Anatomical Variation Assessment in Adaptive Radiation Therapy - Xianjin Dai, Emory University
Patient-specific Auto-segmentation of Target and Organs at Risk on Daily Fan-beam CT Images - Yizheng Chen, Stanford University
Deep Learning Prediction of Liver Toxicity with Dynamic Gadoxetic Acid-enhanced (DGAE) MRI post-SBRT in Hepatocellular Carcinoma - Lise Wei, University of Michigan
Deep Learning (DL) Segmentation of Heart Substructures in RT Planning - Alberto Traverso on behalf of Leonard Nürnberg, Maastro
Xuejun Gu
Break (2:45 PM – 3:00 PM)
3:00 PM – 3:30 PM Data and Data Processing in AI Healthcare Rodney Wiersma
3:30 PM – 4:00 PM AI for QA and Risk Management Gilmer Valdes
4:00 PM – 4:30 PM Ethical and Fair AI for Healthcare David Magnus
4:30 PM – 5:00 PM Open Q&A with Speakers Rodney Wiersma
Gilmer Valdes
David Magnus