Optimizing breast lesions diagnosis and decision-making with a deep learning fusion model integrating ultrasound and mammography: a dual-center retrospective study

Optimizing breast lesions diagnosis and decision-making with a deep learning fusion model integrating ultrasound and mammography: a dual-center retrospective study

Abstract Background This study aimed to develop a BI-RADS network (DL-UM) via integrating ultrasound (US) and mammography (MG) images and explore its performance in improving breast lesion diagnosis and management when collaborating with radiologists, particularly in cases with discordant US and MG...

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Bibliographic Details
Main Authors: Ziting Xu, Shengzhou Zhong, Yang Gao, Jiekun Huo, Weimin Xu, Weijun Huang, Xiaomei Huang, Chifa Zhang, Jianqiao Zhou, Qing Dan, Lian Li, Zhouyue Jiang, Ting Lang, Shuying Xu, Jiayin Lu, Ge Wen, Yu Zhang, Yingjia Li
Format: Article
Language:English
Published: BMC 2025-05-01
Series:Breast Cancer Research
Subjects:
Neural networks
Ultrasonography
Digital mammography
Clinical decision-making
Breast tumours
Online Access:https://doi.org/10.1186/s13058-025-02033-6
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https://doi.org/10.1186/s13058-025-02033-6

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