GLAC-Unet: Global-Local Active Contour Loss with an Efficient U-Shaped Architecture for Multiclass Medical Image Segmentation.
The field of medical image segmentation powered by deep learning has recently received substantial attention, with a significant focus on developing novel architectures and designing effective loss functions. Traditional loss functions, such as Dice loss and Cross-Entropy loss, predominantly rely on...
| Published in: | Journal of Imaging Informatics in Medicine Vol. 38; no. 5; pp. 3198 - 3221 |
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| Main Authors: | , , , , |
| Format: | diagnostic images equations & formulas pictorial research tables/charts Journal Article |
| Published: |
Springer Nature
Oct2025
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| Online Access: | View this record in EBSCOhost |