Chan–Vese aided fuzzy C‐means approach for whole breast and fibroglandular tissue segmentation: Preliminary application to real‐world breast MRI
Our results demonstrated that the CV-aided FCM approach significantly outperformed the existing methods and resulted in significantly more accurate whole breast and FGT segmentation in MRI data.
Authors
- Hongxiang Lin (ORCID: https://orcid.org/0000-0001-6643-327X)
- Chao Rong (ORCID: https://orcid.org/0000-0002-5754-301X)
- Salabat Khan (ORCID: https://orcid.org/0000-0003-1470-0529)
- Syed Furqan Qadri (ORCID: https://orcid.org/0000-0001-9067-054X)
- Syeda Shamaila Zareen (ORCID: https://orcid.org/0000-0001-7085-4675)
- Salman Qadri (ORCID: https://orcid.org/0000-0002-3503-6535)
- Zeyu Zhuang
- Mubashir Ahmad (ORCID: https://orcid.org/0000-0002-4542-1808)
- Jing Li (ORCID: https://orcid.org/0000-0002-8044-2284)
Institutions
- COMSATS University Islamabad (PK)
- Shenzhen University (CN)
- Muhammad Nawaz Shareef University of Agriculture (PK)
- Zhejiang Lab (CN)
- Shenzhen Technology University (CN)
- BGI Research (CN)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-02-05
- DOI
- https://doi.org/10.1002/mp.17660
- Citations
- 10
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 24.81
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Zhejiang Province