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  钱晓华

  长聘（Tenured）副教授、博士生导师。曾为美国德克萨斯大学生物医学信息学院助理教授。吉林大学电子工程和美国杜克大学医学物理专业联合培养博士，并在美国维克森林大学医学院接受博士后训练。现任上海市生物医学工程学会生物医学信息专委会秘书长。目前主持国自然面上（2021，2023）、上海市面上、省级重点研发/科技转化课题、企业横向以及医工交叉等课题，作为骨干参与张江重大项目和上海交大重大项目STAR计划等。

  
  

  实验室（Medical Image and Health Informatics Lab，MIHI)主页：

  https://mihi.sjtu.edu.cn/

1. 主要研究兴趣：

    医学图像处理与分析，人工智能算法研究，包括图像（视频）的细粒度分类与预测，医学图像的检测与分割，以及健康大数据挖掘与分析；主要解决的技术挑战：小样本和细粒度分析，模型的稳定性与泛化性。

    当前主要研究：构建因果推理模型，和医疗基础（大）模型来解决医疗AI领域的核心挑战；并在此基础上，推动医疗AI系统的真正临床应用与落地，服务大众。

2. 主要研究课题：

    1）胰腺癌临床诊断与治疗全过程的影像智能算法体系研究，包括胰腺癌筛查与早期诊断，胰腺癌检测与分割，胰腺癌淋巴转移/良恶性的分析和预测，以及胰腺癌手术可切除性分析等。

2）运动功能视频评估的核心算法体系研究（例如，帕金森病运动迟缓、震颤、僵直、站立平衡和步态等），实现“运动障碍”与“姿势异常”的自动检测与分析，以及在临床诊断与评估、远程医疗和居家管理等方面的应用，并拓展到脑瘫、斜颈、中风、认知障碍等疾病的视频自动评估。此外，还开展运动与认知、运动与康复的评估与干预研究。

欢迎相关课题合作（邮件联系）！

近三年代表作（主要（大）通讯作者）：

(Source codes are available at https://github.com/SJTUBME-QianLab)

1. J. Qu^#, X. Xiao^#, X. Wei*, X. Qian*. A Causality-Inspired Generalized Model for Automated Pancreatic Cancer Diagnosis. Medical Image Analysis, 03, 2024.

2.  X. Tang, R. Guo, C. Zhang, X. Qian*. A Causal Counterfactual Graph Neural Network for Arising-from-Chair Abnormality Detection in Parkinsonians. Medical Image Analysis, 07, 2024.

3. X. Chen^#, W.Wang^#, Y. Jiang^#, X. Qian*. A Dual-transformation with Contrastive Learning Framework for Lymph Node Metastasis Prediction in Pancreatic Cancer. Medical Image Analysis, 85: 102753, 2023.

4. J. Qu, X.Wei*, X. Qian*. Generalized Pancreatic Cancer Diagnosis via Multiple Instance Learning and Anatomically-Guided Shape Normalization. Medical Image Analysis, 86: 102774, 2023.

5.  R. Guo, H. Li, C. Zhang, X. Qian*. A Tree-Structure-Guided Graph Convolutional Network with Contrastive Learning for the Assessment of Parkinsonian Hand Movements. Medical Image Analysis, 81: 102560, 2022.

6. J. Li^#, L. Qi^#, Q. Chen, Y. Zhang, X. Qian*. A Dual Meta-Learning Framework based on Idle Data for Enhancing Segmentation of Pancreatic Cancer. Medical Image Analysis, 78: 102342, 2022.

7. W. Fu^#, H. Hu^#, X. Li, R. Guo, T. Chen, X. Qian*, A Generalizable Causal-Invariance-Driven Segmentation Model for Peripancreatic Vessels. IEEE Transactions on Medical Imaging, 05, 2024.

8. X. Li^#, R. Guo^#, J. Lu^#, T. Chen, X. Qian*. Causality-Driven Graph Neural Network for Early Diagnosis of Pancreatic Cancer in Non-Contrast Computerized Tomography. IEEE Transactions on Medical Imaging, 42(6): 1656-1667, 2023.

9. X. Song^#, J. Li^#, X. Qian*. Diagnosis of Glioblastoma Multiforme Progression via Interpretable Structure-Constrained Graph Neural Networks. IEEE Transactions on Medical Imaging, 42(2): 380-390, 2023.

10. X. Tang, R. Guo, C. Zhang, X. Zhuang*, X. Qian*. A Causality-driven Graph Convolutional Network for Postural Abnormality Diagnosis in Parkinsonians. IEEE Transactions on Medical Imaging, 08, 2023.

11. X. Tang^#, C. Zhang^#, R. Guo, X. Yang*, X. Qian*. A Causality-Aware Graph Convolutional Network Framework for Rigidity Assessment in Parkinsonians. IEEE Transactions on Medical Imaging, 07, 2023.

12. X. Chen, Z. Chen, J. Li, Y. Zhang, X. Lin, X. Qian*. Model-driven deep learning method for pancreatic cancer segmentation based on spiral-transformation. IEEE Transactions on Medical Imaging, 41(1): 75-87, 2022.

13. X. Chen, X. Lin, Q. Shen, X. Qian*. Combined Spiral Transformation and Model-Driven Multi-Modal Deep Learning Scheme for Automatic Prediction of TP53 Mutation in Pancreatic Cancer. IEEE Transactions on Medical Imaging, 40(2): 735-747, 2021.

14. R. Guo^#, Z. Xie^#, C. Zhang, X. Qian*. Causality-Enhanced Multiple Instance Learning with Graph Convolutional Networks for Parkinsonian Freezing-of-Gait Assessment. IEEE Transactions on Image Processing, 06, 2024.

15. R. Guo, X. Shao, C. Zhang, X. Qian*. Multi-scale Sparse Graph Convolutional Network for the Assessment of Parkinsonian Gait. IEEE Transactions on Multimedia, 24: 1583-1594, 2022.

16. R. Guo, L. Wang, C. Zhang, L. Gu, D. Li*, X. Qian*. A Causality-Informed Graph Convolutional Network for Video Assessment of Parkinsonian Leg Agility. IEEE Transactions on Circuits and Systems for Video Technology, 06, 2024.

17. Z. Xie^#, R. Guo^#, C. Zhang, X. Qian*. A Clinically Guided Graph Convolutional Network for Assessment of Parkinsonian Pronation-Supination Movements of Hands. IEEE Transactions on Circuits and Systems for Video Technology, 09, 2023.

18. R. Guo, J. Sun, C. Zhang, X. Qian*. A Contrastive Graph Convolutional Network for Toe-Tapping Assessment in Parkinson’s Disease. IEEE Transactions on Circuits and Systems for Video Technology, 32(12): 8864-8874, 2022.

19. R. Guo^#, J. Sun^#, C. Zhang, X. Qian*. A Self-Supervised Metric Learning Framework for the Arising-from-Chair Assessment of Parkinsonians with Graph Convolutional Networks. IEEE Transactions on Circuits and Systems for Video Technology, 32(9): 6461-6471, 2022.

20. Xinyue Li^#, Rui Guo^#, Hongzhang Zhu^#, Tao Chen, X. Qian*. A Causality-Informed Graph Intervention Model for Pancreatic Cancer Early Diagnosis. IEEE Transactions on Artificial Intelligence, 04, 2024.

21. R. Guo, X. Shao, C. Zhang, X. Qian*. Sparse Adaptive Graph Convolutional Network for Leg Agility Assessment in Parkinson’s Disease. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 28(12): 2837-2848, 2020.

22. J. Li^#, T. Chen^#, X. Qian*. Generalizable Pancreas Segmentation Modeling in CT Imaging via Meta-learning and Latent-space Feature Flow Generation. IEEE Journal of Biomedical and Health Informatics, 27(1): 374-385, 2023.

23. J. Li^#, H. Zhu^#, T. Chen*, X. Qian*. Generalizable Pancreas Segmentation via a Dual Self-Supervised Learning Framework. IEEE Journal of Biomedical and Health Informatics, 27(10): 4780-4791, 2023. (封面文章)

24. J. Li, C. Feng, X.Lin, X. Qian*. Utilizing GCN and Meta-Learning Strategy in Unsupervised Domain Adaptation for Pancreatic Cancer Segmentation. IEEE Journal of Biomedical and Health Informatics, 26(1): 79-89, 2022.

25. X. Song^#, M. Mao^#, X. Qian*. Auto-Metric Graph Neural Network Based on a Meta-learning Strategy for the Diagnosis of Alzheimer's disease. IEEE Journal of Biomedical and Health Informatics, 25(8): 3141-3152, 2021.

26. G. Xu, J. Reboud, Y. Guo, H. Yang, H. Gu, C. Fan*, X. Qian*, Jonathan M Cooper*. Programmable design of isothermal nucleic acid diagnostic assays through abstraction-based models. Nature communications, 13(1): 1-9, 2022. (共同通讯)

数据结构（工科平台，大一）

生物医学工程中的数据挖掘 （研究生课程）

1. 钱晓华; 李钧; 多模态医学图像分割方法、系统、存储介质及电子设备2020-02-24, 中国, CN2020101124914

2. 钱晓华; 陈夏晗; 基于多模态的深度学习预测方法、系统、介质及设备2020-02-18, 中国, CN2020100986849

3. 钱晓华; 陈夏晗; 深度学习中螺旋变换数据扩增方法、系统、介质及设备2020-02-18, 中国, CN202010098682X 

4. 指导学生获2022年第七届上海交通大学研究生“学术之星”提名奖（全校Top 20）

5. 指导学生获2023年上海交通大学研究生“创新之星”

6. 指导学生获2024届上海市优秀毕业生

7. 指导博士、硕士研究生在2021、2022、2023年先后6人次获研究生国家奖学金（占学院推荐名额20%）

10. 指导学生获2022年/2023年上海市女大学生创新创业大赛一等奖/二等奖

11. 课题获2022年第一届医学人工智能创新创业大赛最具创新奖

12. 课题获2023年第二届医学人工智能创新创业大赛科研组价值项目（一等奖）

指导研究生毕业去向

1. 首届毕业博士生，2023年11月入职 西南交通大学，任助理教授

2. 首位出站博士后，2024年2月入职 杭州电子科技大学，任讲师