Differential cell counts using center-point networks achieves human-level accuracy and efficiency over segmentation

Differential cell counts is a challenging task when applying computer vision algorithms to pathology. Existing approaches to train cell recognition require high availability of multi-class segmentation and/or bounding box annotations and suffer in performance when objects are tightly clustered. We p...

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Detalles Bibliográficos
Autores principales: Lee, Sarada M. W., Shaw, Andrew, Simpson, Jodie L., Uminsky, David, Garratt, Luke W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377024/
https://www.ncbi.nlm.nih.gov/pubmed/34413367
http://dx.doi.org/10.1038/s41598-021-96067-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377024/
https://www.ncbi.nlm.nih.gov/pubmed/34413367
http://dx.doi.org/10.1038/s41598-021-96067-3

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