Colon and lung cancer classification from multi-modal images using resilient and efficient neural network architectures

Colon and lung cancer classification from multi-modal images using resilient and efficient neural network architectures

Automatic classification of colon and lung cancer images is crucial for early detection and accurate diagnostics. However, there is room for improvement to enhance accuracy, ensuring better diagnostic precision. This study introduces two novel dense architectures (D1 and D2) and emphasizes their eff...

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Bibliographic Details
Main Authors: A. Hasib Uddin, Yen-Lin Chen, Miss Rokeya Akter, Chin Soon Ku, Jing Yang, Lip Yee Por
Format: Article
Language:English
Published: Elsevier 2024-05-01
Series:Heliyon
Subjects:
Dense neural networks (DNN)
Cancer image classification
Multi-modal network
Histopathological imaging
CT-Scan imaging
Lung cancer
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024066568

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http://www.sciencedirect.com/science/article/pii/S2405844024066568

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