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...

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Veröffentlicht in:	Computer vision and image understanding Jg. 210; S. 103248
Hauptverfasser:	El Jurdi, Rosana, Petitjean, Caroline, Honeine, Paul, Cheplygina, Veronika, Abdallah, Fahed
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.09.2021 Elsevier
Schlagworte:	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-Zugang:	Volltext
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