#MICCAI 2023 decisions are out!

If your paper was rejected, you can resubmit to our workshop. We appreciate contributions in the field of generative models for MIC / CAI and our reviewers will support you with constructive criticism to improve the quality of your manuscripts.

Find our call for papers here:
https://dgm4miccai.github.io

"We are currently missing 1300 reviews (20%)" 😱 #MICCAI

Howdy!

we are happy to announce that not only our #DGM4MICCAI workshop proposal has been accepted for #MICCAI2023 conference, but you can also follow our updates on the #fediverse! 🥳

DGM4MICCAI is a #MICCAI workshop focused on Deep Generative Models for medical applications, organized by a team of international researchers in medical image computing and computer assisted interventions.

Find more info on our webpage:
https://dgm4miccai.github.io/

#Introduction

Howdy!

we are happy to announce that not only our #DGM4MICCAI workshop proposal has been accepted for #MICCAI2023 conference, but you can also follow our updates on the #fediverse! 🥳

DGM4MICCAI is a #MICCAI workshop focused on Deep Generative Models for medical applications, organized by a team of international researchers in medical image computing and computer assisted interventions.

Find more info on our webpage:
https://dgm4miccai.github.io/

Howdy!

We are the social media team of #DGM4MICCAI workshop. We are happy to announce that not only our workshop proposal has been accepted for #MICCAI2023 conference, but you can also follow our updates on the #fediverse! 🥳

DGM4MICCAI is a #MICCAI workshop focused on Deep Generative Models for medical applications, organized by a team of international researchers in medical image computing and computer assisted interventions.

Find more info on our webpage:
https://dgm4miccai.github.io/

The Machine Learning in Medical Imaging proceedings are out! Thanks to all for sharing your research.

Special shoutout to the amazing duo Ana-Teodora Radutoiu and Paula López Diez for leading our paper on deep RL for inner ear localization: "Accurate Localization of Inner Ear Regions of Interests Using Deep Reinforcement Learning"

Published: https://link.springer.com/chapter/10.1007/978-3-031-21014-3_43
Pre-print: https://findit.dtu.dk/en/catalog/63a4b75dd417b726d2dc39b9

#newpaper #deeplearning #rl #dl #ComputerVision #landmarks #cochlea #teosdebut #miccai #hny 🎉

@jmlipman not segmentation, but I also work on AI+neuroimaging (mostly dMRI and tractography)! I've only tagged #neuroimaging, but it's still a very large community. With such an interdisciplinary field, perhaps we can tag conferences like #OHBM or #MICCAI?