Medical Imaging with Deep Learning: MIDL 2020 -- Short Paper Track
Tal Arbel, Ismail Ben Ayed, Marleen de Bruijne, Maxime Descoteaux,, Herve Lombaert, Chris Pal

TL;DR
This collection compiles accepted abstracts from MIDL 2020, highlighting recent advances in deep learning applications for medical imaging, showcasing diverse research contributions presented at the conference.
Contribution
It provides a comprehensive overview of the latest research developments in deep learning for medical imaging as presented at MIDL 2020.
Findings
Diverse deep learning methods for medical imaging
Innovative applications demonstrated at MIDL 2020
Advances in model accuracy and robustness
Abstract
This compendium gathers all the accepted extended abstracts from the Third International Conference on Medical Imaging with Deep Learning (MIDL 2020), held in Montreal, Canada, 6-9 July 2020. Note that only accepted extended abstracts are listed here, the Proceedings of the MIDL 2020 Full Paper Track are published in the Proceedings of Machine Learning Research (PMLR).
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Taxonomy
TopicsRadiomics and Machine Learning in Medical Imaging
