Deep Generative Models workshop @ MICCAI 2022


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 2022 will be all about Deep Generative Models in Medical Image Computing and Computer Assisted Interventions.

Associated Challenge: AdaptOR

The decisions are out: A total of 12 papers were accepted. Congratulations to the authors of all accepted papers.

Submission Details

The online submission for DGM4MICCAI is open until 25. June 2022, 11:59 PM PST. Contributions must be submitted online through the CMT submission system.

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 2022
Review Release 13 July 2022
Final Decision 16 July 2022
Camera ready papers due 27 July 2022
DGM4MICCAI Workshop 22 September 2022

Preliminary Program

DGM4MICCAI workshop will be a half-day event, following the agenda below:
Start End Topic
8:00 AM 8:15 AM Welcome
8:15 AM 8:50 AM Plenary session 1
8:50 AM 9:35 AM Oral session 1 (6 presentations, each oral 5 minutes)
9:35 AM 9:50 AM Coffee break
9:50 AM 10:35 AM Plenary session 2
10:35 AM 11:10 AM Oral session 2 (6 presentations, each oral 5 minutes)
11:10 AM 11:30 PM AdaptOR Challenge results

All times are given in SGT time. Please note that times might be subject to change, so keep an eye on the schedule or follow us on Twitter to be up-to-date.

Keynote Speakers

Michal Rosen-Zvi

IBM Research


Deep generative models for drug discovery

Islem Rekik

Istanbul Technical University


A roadmap to non-invasive brain mapping and diagnosis with/out data