Attention-guided cascaded network with pixel-importance-balance loss for retinal vessel segmentation

Accurate retinal vessel segmentation from fundus images is essential for eye disease diagnosis. Many deep learning methods have shown great performance in this task but still struggle with limited annotated data. To alleviate this issue, we propose an Attention-Guided Cascaded Network (AGC-Net) that...

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Detalles Bibliográficos
Autores principales: Su, Hexing, Gao, Le, Lu, Yichao, Jing, Han, Hong, Jin, Huang, Li, Chen, Zequn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Cell and Developmental Biology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203622/
https://www.ncbi.nlm.nih.gov/pubmed/37228648
http://dx.doi.org/10.3389/fcell.2023.1196191

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203622/
https://www.ncbi.nlm.nih.gov/pubmed/37228648
http://dx.doi.org/10.3389/fcell.2023.1196191

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