Deep structured residual encoder-decoder network with a novel loss function for nuclei segmentation of kidney and breast histopathology images

To improve the process of diagnosis and treatment of cancer disease, automatic segmentation of haematoxylin and eosin (H & E) stained cell nuclei from histopathology images is the first step in digital pathology. The proposed deep structured residual encoder-decoder network (DSREDN) focuses on t...

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Detalles Bibliográficos
Autores principales: Chanchal, Amit Kumar, Lal, Shyam, Kini, Jyoti
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
1197: Advances in Soft Computing Techniques for Visual Information-based Systems
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8809220/
https://www.ncbi.nlm.nih.gov/pubmed/35125928
http://dx.doi.org/10.1007/s11042-021-11873-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8809220/
https://www.ncbi.nlm.nih.gov/pubmed/35125928
http://dx.doi.org/10.1007/s11042-021-11873-1

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