Nuclei segmentation and classification from histopathology images using federated learning for end-edge platform.

Accurate nuclei segmentation and classification in histology images are critical for cancer detection but remain challenging due to color inconsistency, blurry boundaries, and overlapping nuclei. Manual segmentation is time-consuming and labor-intensive, highlighting the need for efficient and scala...

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Bibliographic Details
Main Authors:	Anjir Ahmed Chowdhury, S M Hasan Mahmud, Md Palash Uddin, Seifedine Kadry, Jung-Yeon Kim, Yunyoung Nam
Format:	Article
Language:	English
Published:	Public Library of Science (PLoS) 2025-01-01
Series:	PLoS ONE
Online Access:	https://doi.org/10.1371/journal.pone.0322749
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Nuclei segmentation and classification from histopathology images using federated learning for end-edge platform by Anjir Ahmed Chowdhury, S M Hasan Mahmud, Md Palash Uddin, Seifedine Kadry, Jung-Yeon Kim, Yunyoung Nam

Published 2025-01-01

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Nuclei segmentation and classification from histopathology images using federated learning for end-edge platform.

Nuclei segmentation and classification from histopathology images using federated learning for end-edge platform by Anjir Ahmed Chowdhury, S M Hasan Mahmud, Md Palash Uddin, Seifedine Kadry, Jung-Yeon Kim, Yunyoung Nam

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