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

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

IntroductionAutomatic 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 develop...

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Bibliographic Details
Main Authors: Rashadul Islam Sumon, Subrata Bhattacharjee, Yeong-Byn Hwang, Hafizur Rahman, Hee-Cheol Kim, Wi-Sun Ryu, Dong Min Kim, Nam-Hoon Cho, Heung-Kook Choi
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-05-01
Series:Frontiers in Oncology
Subjects:
computational pathology
nuclei segmentation
histological image
attention mechanism
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2023.1009681/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2023.1009681/full

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