gamUnet: designing global attention-based CNN architectures for enhanced oral cancer detection and segmentation

gamUnet: designing global attention-based CNN architectures for enhanced oral cancer detection and segmentation

IntroductionOral squamous cell carcinoma (OSCC) is a significant global health burden, where timely and accurate diagnosis is essential for improved patient outcomes. Conventional diagnosis relies on manual evaluation of hematoxylin and eosin (H&E)-stained slides, a time-consuming process re...

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Bibliographic Details
Main Authors: Jinyang Zhang, Hongxin Ding, Runchuan Zhu, Weibin Liao, Junfeng Zhao, Min Gao, Xiaoyun Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Medicine
Subjects:
oral squamous cell carcinoma (OSCC)
segmentation
image processing
image classification
convolutional neural networks
deep learning–artificial intelligence
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1582439/full
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https://www.frontiersin.org/articles/10.3389/fmed.2025.1582439/full

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