Effective BCDNet-based breast cancer classification model using hybrid deep learning with VGG16-based optimal feature extraction

Effective BCDNet-based breast cancer classification model using hybrid deep learning with VGG16-based optimal feature extraction

Abstract Problem Breast cancer is a leading cause of death among women, and early detection is crucial for improving survival rates. The manual breast cancer diagnosis utilizes more time and is subjective. Also, the previous CAD models mostly depend on manmade visual details that are complex to gene...

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Bibliographic Details
Main Authors: Meenakshi Devi P., Muna A., Yasser Ali, Sumanth V.
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Medical Imaging
Subjects:
Breast cancer diagnosis model
Ultrasound images
Breast cancer diagnosis network
Atrous spatial pyramid pooling
Random parameterized adaptive opposition slime mould with egret swarm optimization
Online Access:https://doi.org/10.1186/s12880-024-01538-4
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https://doi.org/10.1186/s12880-024-01538-4

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