Robust Bi-CBMSegNet framework for advancing breast mass segmentation in mammography with a dual module encoder-decoder approach

Robust Bi-CBMSegNet framework for advancing breast mass segmentation in mammography with a dual module encoder-decoder approach

Abstract Breast cancer is a prevalent disease affecting millions of women worldwide, and early screening can significantly reduce mortality rates. Mammograms are widely used for screening, but manual readings can lead to misdiagnosis. Computer-assisted diagnosis can help physicians make faster, more...

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Bibliographic Details
Main Authors: Yu Wang, Mudassar Ali, Tariq Mahmood, Amjad Rehman, Tanzila Saba
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Cancer
Deep learning
Mass segmentation
Mass classification
Global and local feature enhancement
Health problem
Online Access:https://doi.org/10.1038/s41598-025-09775-5
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https://doi.org/10.1038/s41598-025-09775-5

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