We are in the process of compiling an archive of all of the entries, together with educational videos from other sources. Stay tuned!

2014 Winners!
Judges 1nd prize
Your friendly guide to human brain atlases
Yiming Xiao and Ian Gerard

Judges 2nd prize
Singular Value Decomposition
Xiao Huang, Xiao Xue, Judith Zimmermann, Piotr Wojewnik

Popular 1st prize
Statistics on Lie groups for Computational Anatomy
Nina Miolane, Bishesh Khanal

Popular 2nd prize
Intraoperative Nuclear Imaging
Asli Okur, Philipp Matthies, Jose Gardiazabal, Oliver Zettinig, Christoph Hennersperger, Richard Brosig, Nassir Navab

2014 Entries: Please look at the 2014 Submissions! All MICCAI 2014 attendees will have the option of voting on these videos during the conference (via a ballot in the program), and can discuss these during the MEC lunch meeting on September 15th.

Deadline Extension: Following many requests, the deadline for the MEC has been extended to August 25th, 2014. Please let us know if you have any questions!


The MICCAI Educational Challenge is a video challenge that will be held for the first time at MICCAI 2014. The goal is to encourage members of the MICCAI community to create educational videos on fundamental concepts in medical image analysis and computer-aided interventions.

The videos should be created by the August deadline (see sidebar). During the main MICCAI conference, we will organize a public event for discussing the challenge and related courseware initiatives. We will also present inaugural MICCAI Education Awards, sponsored by the MICCAI society, for the best videos. There will be two first prizes worth $500 each -- one for a popular vote and one through a expert panel vote --- and two second prizes worth $250 each.

Click here for more details.


Students form a significant part of the MICCAI community, and many of them are still learning the concepts of the field. As there are many fundamental concepts unique to medical image analysis, students would benefit tremendously from introductory courses in the field. Such courses would also benefit researchers more advanced in their careers, willing to be introduced to a new topic in MICCAI. Unfortunately, courses and summer schools in medical imaging are sparse, and finding good sources of educational material at the start of one’s research can be difficult. Recently, online video-based education initiatives, such as the Khan Academy, have demonstrated the potential of short online educational videos. The systems allow students to access the video materials at any time, in order to learn concepts they might not otherwise have access to, for example at their own institutions.

With the MICCAI Educational Challenge, we hope to build a library of such videos relevant to the MICCAI community created by its members. A good collection of these materials will allow the students and other interested researchers to learn the basics of medical image analysis by self-study during the start of their projects, both making the field more accessible and shortening the required start-up time for the students.