ASNR/ASFNR AI workshop


Announcement

Status Update, March 27, 2020:
Because of the circumstances surrounding the spread of COVID-19, the first ASNR/ASFNR AI Workshop on May 30-31 will now be conducted as an online, virtual workshop on the Zoom platform. The participant fee has been reduced to $250. Applicants will be informed of their acceptance into the workshop by March 30. 

Overview

ASNR and ASFNR partner to offer an AI education program to train neuroradiologists and make them effective leaders and collaborators in AI projects focusing on neuroimaging.

The goals of this education program are to:

  1. Serve as a hands-on introductory workshop to AI and deep learning in neuroradiology
  2. Allow attendees to understand and critically evaluate literature in AI and neuroradiology
  3. Allow attendees to set up and conduct a basic research project using AI.

This education program will consist of prerequisite work, two workshops (May 30-31 during ASNR 2020 Annual Meeting and Oct. 8 at the ASFNR 2020 meeting), and a project to be conducted in between the two workshops. Different datasets will be made available for the participants, including the 2019 ASFNR AI challenge dataset and the 2019 RSNA challenge dataset. Participants are free to use these datasets or to select other datasets that are publicly available or that they have access to.

The education program will accept 25 applicants a year, who will graduate at the end of the ASFNR workshop and be invited to join the ASNR/ASFNR AI study group for continued collaboration and networking. Applications for the 2020 workshop are no longer being accepted.

In addition to clinical neuroradiologists and trainees, data scientists and PhD faculty engaged in neuroimaging research are encouraged to apply.

Applicants will be selected based on a competitive application process that will involve submission of a biosketch, letter of motivation, and potential research project topic. Selection process will ensure that a diverse class is created each year, in terms of training levels (fellows, junior faculty, more advanced faculty), institution and geographical representation.

Organizing Committee

  • Daniel Barboriak, Duke
  • Peter Chang, UC Irvine
  • Risto Filippi, Northwell
  • Adam Flanders, Jefferson
  • Christopher Hess, UCSF
  • Yvonne Lui, NYU
  • Max Wintermark, Stanford
  • Greg Zaharchuk, Stanford

Speakers/Mentors

We welcome experienced AI researchers to join our team of speakers who also serve as mentors for the accepted participants. Please apply online if you are interested in helping out with the AI workshop.

Program

Saturday and Sunday, May 30-31, 2020 (virtual workshop held online)
Duration
Block-1 Introduction
30 min Historic Overview of AI and Machine Learning
30 min The Role of Neuroradiologists in AI Research
30 min Survey of Current Applications and Tools
Block-2 30 min Designing a Neuroradiology AI Project
30 min Data Curation and Annotation
30 min Choosing Machine Learning Algorithms
Block-3 30 min Getting Started: Hardware Considerations
30 min Getting Started: Software Considerations
30 min Getting Started: Personnel / Who to Hire
Block-4 30 min Introduction to Python
30 min Introduction to Machine Learning Libraries
30 min Introduction to Artificial Neural Networks
Block-5 30 min Overview of Convolutional Neural Networks
30 min Optimization and Hyperparameters
30 min Common CNN Architectures for Medical Imaging
Block-6 30 min Towards a Scalable AI Research Infrastructure
30 min Advanced Data Annotation Strategies
30 min Ethics of Medical AI
Conclusion and Wrap Up
ASFNR 2019, Thursday, October 8, 2020, Santa Fe, NM (in-person workshop)
Duration
Block-1 Introduction
30 min Progress Report all participants
30 min Participant Presentations I all participants
30 min Participant Presentations II all participants
Block-2 30 min Collaborative Research
30 min Customized CNN Architectures for Medical Imaging
30 min Opportunities in Natural Language Processing
Block-3 30 min Manuscripts/Grants: Putting Together A Paper
30 min Manuscripts/Grants: Understanding Validation and CNN Statistics
30 min Manuscripts/Grants: Clinical Trials/Funding Opportunities
Block-4 30 min FDA and Regulatory Considerations
30 min Fairness in AI
30 min Clinical Deployment
30 min Wrap-up all participants