2022 | Loss odyssey in medical image segmentation
https://malmic.ca/wp-content/themes/osmosis/images/empty/thumbnail.jpg 150 150 MaLMIC - Machine Learning in Medical Imaging Consortium MaLMIC - Machine Learning in Medical Imaging Consortium https://malmic.ca/wp-content/themes/osmosis/images/empty/thumbnail.jpgShort Description: In this paper, we present a comprehensive review of segmentation loss functions in an organized manner. We also conduct the first large-scale analysis of 20 general loss functions on four typical 3D segmentation tasks involving six public datasets from 10+ medical centres. Our code and segmentation results are publicly available and can serve as a loss function benchmark. We hope this work will also provide insights on new loss function development for the community.
Modality: CT
Organ: Liver, Pancreas
Disease: Cancer