ST-Double-Net: A Two-Stage Breast Tumor Classification Model Based on Swin Transformer and Weakly Supervised Target Localization

ST-Double-Net: A Two-Stage Breast Tumor Classification Model Based on Swin Transformer and Weakly Supervised Target Localization

Breast cancer is the second deadliest cancer (after lung cancer) globally among women, with high incidence and mortality rates. Its early diagnosis is pivotal for improving the cure rate. With the continuous development and maturity of deep learning technologies, traditional classification models ha...

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Bibliographic Details
Main Authors: Shengnan Hao, Yihan Jia, Jianuo Liu, Zhiwu Wang, Chunling Liu, Zhanlin Ji, Ivan Ganchev
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Breast tumor classification
Swin Transformer
weakly supervised target localization
heatmap cropping
Online Access:https://ieeexplore.ieee.org/document/10639378/

Internet

https://ieeexplore.ieee.org/document/10639378/

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