December 14th, 2019 - Vancouver Convention Center, Canada

(Saturday Dec 14th, Room: ** West Bldg 301-305 (Top Floor) **)


'Medical Imaging meets NeurIPS' is a satellite workshop established in 2017. The workshop aims to bring researchers together from the medical image computing and machine learning communities. The objective is to discuss the major challenges in the field and opportunities for joining forces. The workshop will feature an oral and poster session where accepted works are presented. In addition, there will be a series of high-profile invited speakers from industry, academia, engineering and medical sciences giving an overview of recent advances, challenges, latest technology and efforts for sharing clinical data.


Medical imaging is facing a major crisis with an ever increasing complexity and volume of data and immense economic pressure. The interpretation of medical images pushes human abilities to the limit with the risk that critical patterns of disease go undetected. Machine learning has emerged as a key technology for developing novel tools in computer aided diagnosis, therapy and intervention. Still, progress is slow compared to other fields of visual recognition which is mainly due to the domain complexity and constraints in clinical applications which require most robust, accurate, and reliable solutions.

Call for Abstracts

We invite submissions of extended abstracts for oral and poster presentation during the workshop. Submitting an abstract is an ideal way of engaging with the workshop and to showcase research in the area of machine learning for medical imaging. Submitted work has to be original but can be of preliminary nature. There will be no workshop proceedings, but accepted abstracts together with author information will be made available on this website (similar to previous years).


  • Submissions: Wednesday, September 11th (4th), 2019 – 23:59 PST – via the online submission system CMT
  • Notifications: Tuesday, October 1st, 2019
  • Workshop: Saturday, December 14th

Live Stream

Live Stream: Here


Call for Abstract