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GLAC-Unet: Global-Local Active Contour Loss with an Efficient U-Shaped Architecture for Multiclass Medical Image Segmentation.

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Title: GLAC-Unet: Global-Local Active Contour Loss with an Efficient U-Shaped Architecture for Multiclass Medical Image Segmentation.
Authors: Trinh, Minh-Nhat1, Tran, Thi-Thao2, Nham, Do-Hai-Ninh3, Lo, Men-Tzung4, Pham, Van-Truong2, truong.phamvan@hust.edu.vn
Source: Journal of Imaging Informatics in Medicine; Oct2025, Vol. 38 Issue 5, p3198-3220, 23p
Database: Applied Science & Technology Source
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  Data: GLAC-Unet: Global-Local Active Contour Loss with an Efficient U-Shaped Architecture for Multiclass Medical Image Segmentation.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Imaging+Informatics+in+Medicine%22">Journal of Imaging Informatics in Medicine</searchLink>; Oct2025, Vol. 38 Issue 5, p3198-3220, 23p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=188953420
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        Value: 10.1007/s10278-025-01387-9
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        Text: English
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      – TitleFull: GLAC-Unet: Global-Local Active Contour Loss with an Efficient U-Shaped Architecture for Multiclass Medical Image Segmentation.
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            NameFull: Nham, Do-Hai-Ninh
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              Text: Oct2025
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              Y: 2025
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