李敏
发布者:     发布时间:2025-09-17    浏览次数:

李敏

undefined

博士,硕士生导师

研究领域:医学图像处理;计算机视觉

办公室&实验室:

电子邮件:MinLi927@163.com

联系电话:

教育背景

  1. 2021/9-2024/12, 新疆大学,计算机科学与技术专业,博士

  2. 2019/9-2021/6, 新疆大学,软件工程专业,硕士

  3. 2017/9-2019/6, 山东女子学院,计算机科学与技术专业,学士

社会工作

  1. 新疆抗癌协会肿瘤人工智能专业委员会 委员

奖励情况

  1. 2024年度“新疆自动化学会科学技术奖”自然科学奖一等奖(排名第一)

主持/参与项目

  1. 新疆维吾尔自治区地州科学基金项目: 基于深度神经网络的多模态图像融合统一应用模型研究(项目编号: 2023D01F27),进行中,主持。

  2. “中央引导地方科技发展专项”: 新疆地区缺血性脑卒中风险筛查及多模态影像人工智能研究服务平台建设(项目编号: ZYYD2023D02),进行中,参与。

  3. “自治区重点研发计划项目”: 基于社会公共服务的数据资源开发利用及安全保障关键技术研发(项目编号:2022B01005),进行中,参与。

学术成果

发表学术论文20余篇 (其中第一作者/共一作者及通信作者9篇)、 获得软件著作权3项、申请发明专利 4 项、主持“地区科学基金”项目1项,参与省部级科研项目2项 。

  1. Li M, Zuo E, Li F, et al. DCFusion: Difference correlation-driven fusion mechanism of infrared and visible images [J]. Pattern Recognition, 2025, 158: 111002. (JCR Q1,第一作者)

  2. Li M, Tuxunjiang P, Li F, et al. MDKFusion: Medical Domain Knowledge-Inspired Area Amplification Network for Multi-Sequence MRI Image Fusion in Ischemic Stroke[C]//2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2024: 2122-2127.(CCF-B 类会议,第一作者)

  3. Li M, Li F, Zuo E, et al. Rethinking the Necessity of Learnable Modal Alignment for Medical Image Fusion[C]//Chinese Conference on Pattern Recognition and Computer Vision (PRCV). Singapore: Springer Nature Singapore, 2024: 596-610. (CCF-C 类会议,第一作者)

  4. Li M, Chen C, Cao Y, et al. CIABNet: Category imbalance attention block network for the classification of multi‐differentiated types of esophageal cancer [J]. Medical Physics, 2023, 50(3): 1507-1527. (JCR Q1,第一作者)

  5. Li M, Nie X, Reheman Y, et al. Computer-aided diagnosis and staging of pancreatic cancer based on CT images[J]. IEEE Access, 2020, 8: 141705-141718.(JCR Q2,第一作者)

  6. Li M, Ma X, Chen C, et al. Research on the auxiliary classification and diagnosis of lung cancer subtypes based on histopathological images[J]. Ieee Access, 2021, 9: 53687-53707. (JCR Q2,第一作者)

  7. Li M, Zuo E, Pahati T, et al. Expert Knowledge-Guide Progressive Learning Network for Medical Image Fusion in Ischemic Stroke [J]. Engineering Applications of Artificial Intelligence,2024. (JCR Q1,第一作者,审稿中)

  8. Chen Q, Li M, Chen C, et al. MDFNet: application of multimodal fusion method based on skin image and clinical data to skin cancer classification [J]. Journal of Cancer Research and Clinical Oncology, 2023, 149(7): 3287-3299. (JCR Q3,共一作者)

  9. Li F, Li M, Zuo E, et al. Self-contrastive Feature Guidance Based Multidimensional Collaborative Network of metadata and image features for skin disease classification[J]. Pattern Recognition, 2024, 156: 110742.(JCR Q1,第二作者)

  10. Liu K, Li M, Chen C, et al. DSFusion: infrared and visible image fusion method combining detail and scene information[J]. Pattern Recognition, 2024, 154: 110633.(JCR Q1,第二作者)

  11. Liu K, Li M, Zuo E, et al. ASFFuse: Infrared and visible image fusion model based on adaptive selection feature maps[J]. Pattern Recognition, 2024, 149: 110226.(JCR Q1,第二作者)

  12. Li F, Zuo E, Chen C, et al. MLDF-Net: Metadata based multi-level dynamic fusion network[C]//Chinese Conference on Pattern Recognition and Computer Vision (PRCV). Singapore: Springer Nature Singapore, 2023: 461-473.(CCF-C 类会议,通信作者)

  13. Li W, Lv X, Zhou Y, et al. SeACPFusion: An Adaptive Fusion Network for Infrared and Visible Images based on brightness perception[J]. Infrared Physics & Technology, 2024, 142: 105541.(JCR Q2,通信作者)