A deep learning ICDNET architecture for efficient classification of histopathological cancer cells using Gaussian noise images

A deep learning ICDNET architecture for efficient classification of histopathological cancer cells using Gaussian noise images

Histopathology image classification is crucial in pathological diagnosis workflow for early detection and treatment. The integration of deep learning technology has greatly improved diagnostic accuracy and efficiency. However, there are limitations when morphological features are not obvious in path...

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Bibliographic Details
Main Authors: Hui Zong, Wenlong An, Xin Chen, Zhanhui Yang, Heng Zhou, Xiangchao Liu, Jianchu Lin, Chuanyue Zong
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Alexandria Engineering Journal
Subjects:
Internal Communication Network with Dual Self-Attention (ICDNET)
Internal Communication Hierarchical Fusion (ICHF)
Efficient Dual Self-Attention (EDA)
Feature fusion
Histopathological images
Gaussian noise
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016824012468
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