Self-relabeling for noise-tolerant retina vessel segmentation through label reliability estimation

BACKGROUND: Retinal vessel segmentation benefits significantly from deep learning. Its performance relies on sufficient training images with accurate ground-truth segmentation, which are usually manually annotated in the form of binary pixel-wise label maps. Manually annotated ground-truth label map...

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Detalles Bibliográficos
Autores principales: Li, Jiacheng, Li, Ruirui, Han, Ruize, Wang, Song
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8753937/
https://www.ncbi.nlm.nih.gov/pubmed/35022020
http://dx.doi.org/10.1186/s12880-021-00732-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8753937/
https://www.ncbi.nlm.nih.gov/pubmed/35022020
http://dx.doi.org/10.1186/s12880-021-00732-y

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