·         医学信号处理（深度学习，医疗影像大数据，影像组学，医学影像处理）

·         人工智能辅助诊断（基于磁共振、超声、CT的人工智能辅助诊断系统）

·         医学超声成像（成像原理、方法，非线性超声成像）

主持项目：

• 国家自然科学基金面上项目 82382096
• 国家自然科学基金重大研究计划91959127
• 国家自然科学基金面上项目61471125
• 上海市科技创新行动计划19441903100
• 国家重点基础研究发展计划2015CB755500项目PI
• 国家自然科学基金青年项目81101049
• 上海市浦江人才计划12PJ1401200
• 教育部博士点基金20110071120019
• 复旦大学专用集成电路与系统国家重点实验室自主课题面上课题11MS007

招生方向：

博士：生物医学工程      专业学位工程博士

硕士：生物医学工程      电路与系统         专业学位工程硕士

• 中国仪器仪表学会副主任委员
• 中国生物医学工程学会青年委员会委员
• 中国声学学会委员
• 中国生物医学工程学会委员
• 上海生物医学工程学会委员

• 2023入选斯坦福全球2%顶尖科学家；
• 2023获中国国际高新技术成果交易会优秀产品奖；
• 2021中国生物医学工程竞赛一等奖；
• 2020复旦大学信息科学与工程学院院长奖;
• 2019欧洲放射高被引论文奖；
• 2019中国生物医学工程竞赛一等奖；
• 2018复旦大学信息科学与工程学院院长奖;
• 2017中国生物医学工程会议优秀论文奖；
• 2015仪器仪表学会优秀论文奖；
• 2015年上海市自然科学三等奖；
• 2014年信息学院优秀工作者；
• 2013年信息学院二等奖教金；
• 2012入选浦江人才计划；
• 2011国际无线电联盟授予Young Scientist Award；
• 2009年复旦大学优秀博士论文奖

• 2015.12 -: 复旦大学电子工程系教授 博导
• 2011.2 至 2015.11 : 复旦大学电子工程系副研究员
• 2008.7 至 2010.8: University of Missouri博士后研究员
• 2008.6: 获复旦大学医学电子学专业博士学位
• 2003.6: 获云南大学通信与信息系统专业硕士学位
• 2000.6: 获云南大学电子学与信息系统专业学士学位

• 本科生课程：概率、数理统计与随机过程（卓越工程师班、智能科学与技术）， 医学超声技术
• 研究生课程：系统匹配与连接
• 博士生课程：信号、图像处理及其在医学中应用

 部分论文：

1.         Zhao Yao, Ting Luo, Yijie Dong, Xiaohong Jia, Yinhui Deng, GuoqingWu, Ying Zhu, Jingwen Zhang, Juan Liu, Lichun Yang, Xiaomao Luo, Zhiyao Li, Yanjun Xu, Bin Hu, Yunxia Huang, Cai Chang, Jinfeng Xu, Hui Luo, Fajin Dong, Xiaona Xia, Chengrong Wu, Wenjia Hu, Gang Wu, Qiaoying Li, Qin Chen, Wanyue Deng, Qiongchao Jiang, Yonglin Mou, Huannan Yan, Xiaojing Xu, Hongju Yan, Ping Zhou, Yang Shao, Ligang Cui, Ping He, Linxue Qian, Jinping Liu, Liying Shi, Yanan Zhao, Yongyuan Xu, Weiwei Zhan, Yuanyuan Wang, Jinhua Yu*, Jianqiao Zhou*. Virtual elastography ultrasound via generative adversarial network for breast cancer diagnosis. Nature Communication, 2023, 14: 788, 12 pages.

2.         Xuan Xie, Chao Shen, Xiandi Zhang, Guoqing Wu, Bojie Yang, Zengxin Qi, Qisheng Tang, Yuanyuan Wang, Hong Ding*, Zhifeng Shi*, Jinhua Yu*. Rapid intraoperative multi-molecular diagnosis of glioma with ultrasound radio frequency signals and deep learning. EBioMedicine, 2023, 98:104899.

3.         Yinhui Deng#, Quan Tao#, Qisheng Tang#, Yinlong Liu#, Hui Dong, Zhifeng Shi, Xiaoming Xie, Weiqi Wang*, Liangfu Zhou*, Jinhua Yu*. Detection of the characteristic magnetic signal of paclitaxel and its application in the inhibition of glioma cells, Fundamental Research, 2023.

4.         Guoqing Wu#, Zhifeng Shi#, Zeyang Li, Xuan Xie, Qisheng Tang, Jingjing Zhu, Zhong Yang, Yuanyuan Wang, Jinsong Wu*, Jinhua Yu*. Study of radiochemotherapy decision‑making for young high‑risk low‑grade glioma patients using a macroscopic and microscopic combined radiomics model. European Radiology, doi.org/10.1007/s00330-023-10378-9, 2023.

5.         Yini Huang#, Zhao Yao#, Lingling Li, Rushuang Mao, Weijun Huang, Zhengming Hu, Yixin Hu, Yun Wang, Ruohan Guo, Xiaofeng Tang, Liang Yang, Yuanyuan Wang, Rongzhen Luo, Jinhua Yu*, Jianhua Zhou*, Deep learning radiopathomics based on preoperative US images and biopsy whole slide images can distinguish between luminal and non-luminal tumors in early-stage breast cancers. eBioMedicine, 2023, 94: 104706.

6.         Leyin Li#, Zhaoyu Hu#, Yunqian Huang#, Wenqian Zhu, Chengqian Zhao, Yuanyuan Wang, Man Chen*, Jinhua Yu*. BP-Net: Boundary and Perfusion Feature Guided Dual-Modality Ultrasound Video Analysis Network for Fibrous Cap Integrity Assessment. Computerized Medical Imaging and Graphics, 2023, 107, 102246.

7.         Zhaoyu Hu, Leyin Li, An Sui, Guoqing Wu, Yuanyuan Wang, Jinhua Yu*. An efficient R-Transformer network with dual encoders for brain glioma segmentation in MR images. Biomedical Signal Processing and Control, 2023, 79, 104034, 1-10.

8.         Wenjia Duan, Cong Wang, Yiqing Jiang, An Sui, Zhi Li, Lu Wang, Zuhai Lei, Silvio Aime, Jinhua Yu*, Cong Li*. A Ratiometric SERS Probe for Imaging the Macrophage Phenotypes in Live Mice with Epilepsy and Brain Tumor. Advanced Healthcare Materials, 2023, 2301000.

9.         Ziyi Jin, Qi Yue, Wenjia Duan, An Sui, Botao Zhao, Yinhui Deng, Yuting Zhai, Yuwen Zhang, Tao Sun, Guang-Ping Zhang, Limei Han, Ying Mao*, Jinhua Yu*, Xiao-Yong Zhang*, Cong Li*. Intelligent SERS Navigation System Guiding Brain Tumor Surgery by Intraoperatively Delineating the Metabolic Acidosis. Advanced Science. 2022 Jan 12; e2104935.

10.     Guoqing Wu, Xi Chen, Zhifeng Shi, Dachuan Zhang, Zhaoyu Hu, Ying Mao, Yuanyuan Wang, Jinhua Yu*. Convolutional neural network with coarse-to-fine resolution fusion and residual learning structures for cross-modality image synthesis. Biomedical Signal Processing and Control, 2022, 21, 103199, 1-12.

11.     Xi Chen#, Yu Lei#, Jiabin Su, Heng Yang, Wei Ni, Jinhua Yu*, Yuxiang Gu*, Ying Mao. A Review of Artificial Intelligence in Cerebrovascular Disease Imaging: Applications and Challenges. Current Neuropharmacology, 2022, 20 (7): 1359-1382.

12.     Nidan Qiao#, Damin Yu#, Guoqing Wu#, Qilin Zhang, Boyuan Yao, Min He, Hongying Ye, Zahoyun Zhang, Yongfei Wang, Hanfeng Wu*, Yao Zhao*, Jinhua Yu*. Low‐rank fusion convolutional neural network for prediction of remission after stereotactic radiosurgery in patients with acromegaly: a proof‐of‐concept study. Journal of Pathology. 2022, 258 (1): 49-57.

13.     An Sui, Yinhui Deng, Yuanyuan Wang, Jinhua Yu*. A deep learning model designed for Raman spectroscopy with a novel hyperparameter optimization method. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. 2022, 280, 121560.

14.     Leyin Li^#, Zhaoyu Hu^#, Yunqian Huang^#, Wenqian Zhu, Yuanyuan Wang, Man Chen*, Jinhua Yu*. Automatic multi-plaque tracking and segmentation in ultrasonic videos. Medical Image Analysis, 2021:102201.

15.     Zhaoyu Hu#, Qiyuan Zhuang#, YangXiao#, Guoqing Wu, Zhifeng Shi, Liang Chen, Yuanyuan Wang, Jinhua Yu *. MIL Normalization —— Prerequisites for Accurate MRI Radiomics Analysis. Computers in Biology and Medicine, 2021:104403.

16.     Jieyang Jin^#, Zhao Yao^#, Ting Zhang, Jie Zeng, Lili Wu, Manli Wu, Jinfen Wang, Yuanyuan Wang, Jinhua Yu *, Rongqin Zheng*. Deep learning radiomics model accurately predicts hepatocellular carcinoma occurrence in chronic hepatitis B patients: a five-year follow-up. Am J Cancer Res. 2021, 11(2): 576-589

17.     Guoqing Wu^#, Xi Chen^#, Jixian Lin, Yuanyuan Wang*, Jinhua Yu*. Identification of invisible ischemic stroke in non-contrast CT based on novel two-stage convolutional neural network model. Medical Physics. 2021, 48(3): 1262-1275.

18.     Jinhua Yu, Yinhui Deng, Tongtong Liu, Jin Zhou, Xiaohong Jia, Tianlei Xiao, Shichong Zhou, Jiawei Li, Yi Guo, Yuanyuan Wang, Jianqiao Zhou, Cai Chang. Lymph node metastasis prediction of papillary thyroid carcinoma based on transfer learning radiomics. Nature Communication, 2020, 11: 4807, 10 pages.

19.     Xueyi Zheng^#, Zhao Yao^#, Yini Huang^#, Yanyan Yu^#, Yun Wang, Yubo Liu, Rushuang Mao, Fei Li, Yang Xiao, Yuanyuan Wang, Yixin Hu, Jinhua Yu*, Jianhua Zhou*. Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer. Nature Communication, 2020, 11: 1236, 9 pages.

20.     Yang Xiao, Congzhi Wang, Yang Sun, Xiangnan Zhang, Ligang Cui, Jinhua Yu*, Hairong Zheng*. Quantitative estimation of passive elastic properties of individual skeletal muscle in vivo using normalized elastic modulus-length curve. IEEE Trans. Biomedical Engineering, 2020, 67,12: 3371-3379.

21.     Liyun Xue^#, Zhuoyun Jiang^#, Tiantian Fu, Qingmin Wang, Yuli Zhu, Meng Dai, Wenping Wang, Jinhua Yu*, Hong Ding*. Transfer Learning Radiomics Based on Multimodal Ultrasound Imaging for Staging Liver Fibrosis. European Radiology, 2020, 2020, 30:2973-2983.

22.     Huigao Luo, Qiyuan Zhuang, Yuanyuan Wang, Aibaidula Abudumijiti, Kuangyu Shi, Axel Rominger, Hong Chen, Zhong Yang, Vanessa Tran, Guoqing Wu, Zeju Li, Zhen Fan, Zengxin Qi, Yuxiao Guo, Jinhua Yu*, Zhifeng Shi*. A novel image signature-based radiomics method to achieve precise diagnosis and prognostic stratification of gliomas. Laboratory Investigation, 2020, doi.org/10.1038/s41374-020-0472-x.

23.     Xi Chen^#, Zhen Fan^#, Kay Ka-Wai Li, Guoqing Wu, Zhong Yang, Xin Gao, Yingchao Liu, Haibo Wu, Hong Chen, Qisheng Tang, Liang Chen, Yuanyuan Wang, Ying Mao, Ho-Keung Ng, Zhifeng Shi, Jinhua Yu*, and Liangfu Zhou. Molecular subgrouping of medulloblastoma based on few-shot learning of multitasking using conventional MR images: a retrospective multicenter study. Neuro-Oncology Advances, 2020, 2(1): doi:10.1093/noajnl/vdaa079.

24.     Yuan Gao^#, Yingchao Liu^#, Yuanyuan Wang*, Zhifeng Shi, Jinhua Yu *. A universal intensity standardization method based on a many-to-one weak-paired cycle generative adversarial network for magnetic resonance images. IEEE transactions on medical imaging, 2019, 38(9): 2059-2069.

25.     Guoqing Wu^#, Yinsheng Chen^#, Yuanyuan^# Wang*, Jinhua Yu *, Xiaofei Lv, Xue Ju, Zhifeng    Shi, Liang Chen, Zhongping Chen. Sparse representation-based radiomics for the diagnosis of brain tumors. IEEE Transactions on Medical Imaging, 2018, 37(4): 893-905.

26.     Jinhua Yu, Zhifeng Shi, Yuxi Lian,Zeju Li, Yuan Gao, Yuanyuan Wang, Liang Chen, Ying Mao. Noninvasive IDH1 mutation estimation based on quantitative radiomics approach for grade II glioma. European Radiology, 2017, 27(8): 3509-3522.