Deep Generative Models workshop @ MICCAI 2021


Deep generative models such as Generative Adversarial Network (GAN) and Variational Auto-Encoder (VAE) are currently receiving widespread attention from not only the computer vision and machine learning communities, but also in the MIC and CAI community. These models combine the advanced deep neural networks with classical density estimation (either explicit or implicit) for achieving state-of-the-art results. DGM4MICCAI workshop at MICCAI 2021 will be all about Deep Generative Models in Medical Image Computing and Computer Assisted Interventions.

Associated Challenge: AdaptOR

Click Here to submit your workshop paper

Submission deadline: 25. June 2021

Submission Details

We seek contributions that include, but are not limited to:

We particularly welcome papers driven by the theme "MIC meets CAI". Interesting novel applications of deep generative models in MIC and CAI beyond these topics are also welcome.

Workshop proceedings are published as part of Springer Nature's Lecture Notes in Computer Science (LNCS) series. Manuscripts will be reviewed in double-blinded peer-review. Please prepare your workshop papers according to the MICCAI submission guidelines (LNCS template, 8 pages maximum).
Supplementary material: PDF documents or mp4 videos, 10 MB maximum file size.


Event Date
Paper Submission Deadline 25. June 2021
Review Release 11. July 2021
Rebuttal Due 14. July 2021
Final Decision 16. July 2021
DGM4MICCAI Workshop 1. October 2021


Start End Topic
2:00 PM2:10 PMWelcome
2:10 PM2:40 PMPlenary Session
2:40 PM3:40 PMOral Session 1
3:40 PM4:10 PMCoffee Break + Poster Session
4:10 PM4:40 PMPlenary Session
4:40 PM5:40 PMOral Session 2
5:40 PM5:50 PMAnnouncing Winners of AdaptOR Challenge
5:50 PM6:00 PMClosing Remarks

All times are given in UTC time.

Download iCal Event

Keynote Speakers

Andreas Maier
Pattern Recognition Lab
FAU Nürnberg, Germany
Stefanie Speidel
Translational Surgical Oncology
NCT Dresden, Germany