Work

SCAR-Net-assisted ultrasound diagnosis of postoperative scars and recurrent lesions in breast cancer

Year: 2026

Type: article

Abstract: < 0.001). The model also demonstrated superior segmentation accuracy with Dice coefficients of 0.918-0.925 compared to traditional methods (0.795-0.811). These results suggest SCAR-Net could serve as a valuable auxiliary tool for improving early recurrence detection in postoperative breast cancer follow-up, potentially reducing unnecessary biopsies and enabling more timely interventions.

Source: iScience

DOI: 10.1016/j.isci.2026.115550

Authors: Na Feng, Shanshan Zhao, Zhikai Lei, Dan Yi, Jincao Yao, Xiao Zhang, Xiangyang Li, Weijie Zou, Jian Zhang, Liyu Chen, Chen Yang, Dong Xu, Yong Wu

Institutions: Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine, Chinese Academy of Sciences, Shaoxing People's Hospital, Zhejiang University, Zhejiang Chinese Medical University, Zhejiang Provincial Hospital of TCM, Wenzhou Medical University

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,240

Funders: Department of Health of Zhejiang Province, Zhejiang Cancer Hospital

Awards: G150603341, G1661659829, G5473795632, G8381846382

OpenAlex ID: W7147143870

FWCI:

Cites: 30

Cited by:

Related to: