Medical Imaging meets NIPS

Saturday, December 9th - Long Beach Convention Center, USA


'Medical Imaging meets NIPS' is a satellite workshop at NIPS 2017. The workshop aims to bring researchers together from the medical image computing and machine learning community. The objective is to discuss the major challenges in the field and opportunities for joining forces. The event will feature a series of high-profile invited speakers from industry, academia, engineering and medical sciences who aim to give 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 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 does not have to be original and can be already published elsewhere and/or can be of preliminary nature. There will be no workshop proceedings, and the poster session may be conditional on receiving sufficiently many submissions. Accepted abstracts together with author information will be made available on this website.


  • Submissions: Sunday, October 29th, midnight PST
  • Notifications: Sunday, November 5th
  • Workshop: Saturday, December 9th, 8:45 AM - 6 PM


Ben Glocker, Imperial College London

Ender Konukoglu, ETH Zurich

Hervé Lombaert, ETS Montreal – Inria

Kanwal Bhatia, Visulytix