Densely Convolutional Spatial Attention Network for nuclei segmentation of histological images for computational pathology

INTRODUCTION: Automatic nuclear segmentation in digital microscopic tissue images can aid pathologists to extract high-quality features for nuclear morphometrics and other analyses. However, image segmentation is a challenging task in medical image processing and analysis. This study aimed to develo...

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Detalles Bibliográficos
Autores principales: Islam Sumon, Rashadul, Bhattacharjee, Subrata, Hwang, Yeong-Byn, Rahman, Hafizur, Kim, Hee-Cheol, Ryu, Wi-Sun, Kim, Dong Min, Cho, Nam-Hoon, Choi, Heung-Kook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248729/
https://www.ncbi.nlm.nih.gov/pubmed/37305563
http://dx.doi.org/10.3389/fonc.2023.1009681

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248729/
https://www.ncbi.nlm.nih.gov/pubmed/37305563
http://dx.doi.org/10.3389/fonc.2023.1009681

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