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...
| Publicado en: | Journal of Imaging Informatics in Medicine Vol. 38; no. 5; pp. 3198 - 3221 |
|---|---|
| Autores principales: | , , , , |
| Formato: | diagnostic images equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Oct2025
|
| Acceso en línea: | Ver este registro en EBSCOhost |