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Multimodal automated diagnosis of lymphovascular invasion in breast cancer on contrast-enhanced MRI: ResUNet + + segmentation and transformer-based classification

Crossref DOI link: https://doi.org/10.1186/s12880-026-02706-4

Published Online: 2026-09-08

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Lin, Junyu

Ma, Zichang

Tao, Yuxi

Liang, Yun

Wei, Yuhan

Liu, Huajin

Zhang, Yaqin
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (81801809)

Basic and Applied Basic Research Foundation of Guangdong Province (No.2020A1515010572)

Zhuhai Basic and Applied Basic Research Project Foundation (ZH22017003200001PWC)
License Information

Text and Data Mining valid from 2026-09-08

Accepted Manuscript valid from 2026-09-08
More Information

Article History

Received: 15 October 2025

Accepted: 13 August 2026

First Online: 8 September 2026

Declarations

Ethics approval and consent to participate: Ethical approval for this retrospective study was granted by the Medical Ethics Committee of the Fifth Affiliated Hospital of Sun Yat-sen University (Approval No. K243-1), in accordance with the Declaration of Helsinki (as revised in 2013). The ethics committee waived the requirement for individual informed consent given the retrospective nature of this study using routinely collected clinical data and biospecimens.

Consent for publication: Not applicable.

Competing interests: The authors declare no competing interests.

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