High-level prior-based loss functions for medical image segmentation: A survey

Today, deep convolutional neural networks (CNNs) have demonstrated state of the art performance for supervised medical image segmentation, across various imaging modalities and tasks. Despite early success, segmentation networks may still generate anatomically aberrant segmentations, with holes or i...

Full description

Saved in:

Bibliographic Details
Published in:	Computer vision and image understanding Vol. 210; p. 103248
Main Authors:	El Jurdi, Rosana, Petitjean, Caroline, Honeine, Paul, Cheplygina, Veronika, Abdallah, Fahed
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.09.2021 Elsevier
Subjects:	Anatomical constraint losses Artificial Intelligence Computer Science Computer Vision and Pattern Recognition Computers and Society Convolutional neural networks Deep learning Engineering Sciences Machine Learning Mathematics Medical image segmentation Neural and Evolutionary Computing Prior-based loss functions Signal and Image processing Statistics Deep learning Anatomical constraint losses Convolutional neural networks Medical image segmentation Prior-based loss functions
ISSN:	1077-3142, 1090-235X
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!