Work

Enhancing semi‐supervised learning for fine‐grained 3D cerebrovascular segmentation with cross‐consistency and uncertainty estimation

Year: 2025

Type: article

Source: Medical Physics

DOI: 10.1002/mp.70017

Authors: Yousuf Babiker M. Osman, Cheng Li, Nazik Elsayed, Alou Diakite, Shuqiang Wang, Shuqiang Wang, Shanshan Wang, Shanshan Wang

Institutions: Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, University of Chinese Academy of Sciences

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: National Natural Science Foundation of China, Youth Innovation Promotion Association of the Chinese Academy of Sciences, Key Laboratory for Magnetic Resonance and Multimodality Imaging of Guangdong Province, National Key Research and Development Program of China, Shenzhen Science and Technology Innovation Program

Awards: G1621403797, G2498043285, G3802261625, G4272704234, G998417102

OpenAlex ID: W4414436009

FWCI: 1.443

Cites: 33

Cited by: 4

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