ASNR/ASFNR AI workshop
ASNR and ASFNR continue to 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:
- Serve as a hands-on introductory workshop to AI and deep learning in neuroradiology
- Allow attendees to understand and critically evaluate literature in AI and neuroradiology
- Allow attendees to set up and conduct a basic research project using AI.
This education program will consist of prerequisite work, two workshops (May 22-23 during the ASNR 2021 Annual Meeting and September 18 at the ASFNR 2021 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.
A total award of $15,000 will be distributed to participants whose projects in the workshop are deemed to have the highest potential for future research in the field of AI applied to neuroradiology. These awards will be presented at the conclusion of the second part of the workshop.
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.
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, as well as the completion of a questionnaire and some pre-requisite work. The 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, as well as level of programming knowledge (a minimum level of programming knowledge will be required).
The application deadline was February 28, 2021 at 11:00 p.m. EDT. Applications are now closed.
PLEASE NOTE UPDATE DATE: Applicants will be informed of selection for the workshop by April 16, 2021.
- 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
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.
|Saturday and Sunday, May 22-23, 2021 (virtual workshop held online)|
|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 2021, Saturday, September 18, 2021, Santa Fe, NM (in-person workshop)|
|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|