代表性成果
科研项目:
[1] 国家自然科学基金重点项目,61835015,调控血管靶向光动力治疗实时在体光学相干成像造影关键技术研究,2019.01-2023.12,278万,结题,参与。
[2] 北京市自然科学基金面上项目,7222309,光动力治疗宫颈癌前病变的光敏剂空间分布定量监测方法研究,2022.01-2024.12,20 万,结题,参与。
[3] 解放军总医院医疗大数据与人工智能研发项目,2019MBD-011,基于深度学习的鲜红斑痣临床辅助决策系统研究,2019.12-2021.12,30万,结题,参与。
[4] 7790.cn必发集团博士科研启动项目,YAU202513461,鲜红斑痣智能诊疗决策关键技术研究,2026.01-2028.12,40 万,在研,主持。
学术论文:
[1] J. Mu, Y. Lin, X. Meng, J. Fan, D. Ai, D. Chen, H. Qiu, J. Yang, Y. Gu, M-CSAFN: Multi-color Space Adaptive Fusion Network for Automated Port-wine Stains Segmentation, IEEE Journal of Biomedical and Health Informatics, 27 (2023) 3924-3935. (SCI, 中科院 1 区Top, JCR 1 区)
[2] J. Mu, Y. Wang, H. Song, X. Meng, Y. Li, J. Fan, D. Ai, D. Chen, H. Qiu, J. Yang, Y. Gu, FCF-CSM: A Fuzzy Clustering Framework Based on Chromaticity Statistical Model for Automatic Segmentation of Port Wine Stains, IEEE Transactions on Automation Science and Engineering, 22 (2025) 12986-12999. (SCI, 中科院 2 区, JCR 1 区)
[3] 穆锦荣, 顾瑛. 基于监督学习半自动检测鲜红斑痣病灶的方法[J]. 中国激光医学杂志, 2018, 27(02): 103.
[4] X. Meng, H. Yu, J. Fan, J. Mu, H. Chen, J. Luan, M. Xu, Y. Gu, G. Ma, and J. Yang, “A self-supervised representation learning paradigm with global content perception and peritumoral context restoration for MRI breast tumor segmentation,” Biomedical Signal Processing and Control, vol. 107, pp. 107757, 2025. (SCI, 中科院 2 区, JCR 1 区)
[5] X. Meng, J. Fan, H. Yu, J. Mu, Z. Li, A. Yang, B. Liu, K. Lv, D. Ai, and Y. Lin, “Volume-awareness and outlier-suppression co-training for weakly-supervised MRI breast mass segmentation with partial annotations,” Knowledge-Based Systems, pp. 109988, 2022. (SCI, 中科院 1 区 Top, JCR 1 区)
[6] Liu X, Mu J, Wang W. An Analogue-difference method and application to induction motor models[J]. Journal of Nonlinear Modeling and Analysis, 2021, 3(4) :505–521.
[7] Zheng, Y., Ai, D., Mu, J. et al. Automatic liver segmentation based on appearance and context information. BioMedical Engineering OnLine 16, 16 (2017). https://doi.org/10.1186/s12938-016-0296-5 (SCI, 中科院 4 区)
申请专利:
[1] 林毓聪, 穆锦荣, 宋红, 杨健. 基于多色彩空间自适应融合的鲜红斑痣分割方法及装置: 中国, CN115063383B[P]. 2025-08-15. (已授权)
[2] 王媛媛, 穆锦荣, 杨健, 等. 一种皮损病灶分割方法、装置、设备及存储介质: 中国, 202311490920.1[P], 2024-02-02.