Divide-and-Attention Network for HE-Stained Pathological Image Classification

SIMPLE SUMMARY: We propose a Divide-and-Attention network that can learn representative pathological image features with respect to different tissue structures and adaptively focus on the most important ones. In addition, we introduce deep canonical correlation analysis constraints in the feature fu...

Descripción completa

Detalles Bibliográficos
Autores principales: Yan, Rui, Yang, Zhidong, Li, Jintao, Zheng, Chunhou, Zhang, Fa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9311575/
https://www.ncbi.nlm.nih.gov/pubmed/36101363
http://dx.doi.org/10.3390/biology11070982

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9311575/
https://www.ncbi.nlm.nih.gov/pubmed/36101363
http://dx.doi.org/10.3390/biology11070982

Ejemplares similares