D2CBDAMAttUnet: Dual-Decoder Convolution Block Dual Attention Unet for Accurate Retinal Vessel Segmentation From Fundus Images
Gathering detailed morphological information from retinal blood vessels is crucial in clinical diagnostics, enabling doctors to make precise assessments of patient conditions and to devise custom treatments. Traditional methods of segmenting these vessels from fundus images are not only tedious but...
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Main Authors: | , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10855415/ |
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