教授名录

张麒博士，教授

办公室：

上海大学宝山校区（东区）翔英楼803室

通信地址(邮政编码):

上海市上大路99号83信箱（200444）

电话：

021-66137256

电子邮件：

zhangq@shu.edu.cn ; zhangq@t.shu.edu.cn

个人主页：

https://scie.shu.edu.cn/Prof/zhangq.htm

张麒，上海大学教授、博士生导师，通信与信息工程学院电子信息工程系副主任，上海市高层次人才。获复旦大学电子工程系学士、博士学位，曾公派至美国杜克大学、英国爱丁堡大学进行访问研究。研究方向为医学图像分析、计算机视觉与智能诊疗技术。发表SCI论文70篇，含2篇ESI高被引论文；主持国家自然科学基金4项，包括国际合作与交流项目、面上项目、青年项目，并主持来源于复旦大学附属华山医院、中山医院、司法鉴定科学研究院、百度等知名医院与企事业单位的横向项目，依托医学大数据研发智能诊疗系统解决临床问题。任上海市医疗图像与医学知识图谱人工智能重点实验室学术委员会委员、中国生物医学工程学会青年委员会委员、上海市医学会超声医学分会人工智能学组副组长，获湖北省科技进步奖二等奖。

教育背景：

2005.9 - 2010.7

复旦大学电子工程系医学电子学，工学博士，导师汪源源教授

2008.8 - 2009.8

美国杜克大学(Duke University)生物医学工程系

联合培养博士生(国家留学基金委公派)，导师Morton Friedman教授

2001.9 - 2005.7

复旦大学电子工程系电子信息科学与技术，理学学士

工作经历：

2020.3 - 今	上海大学通信与信息工程学院，教授
2013.3 - 2020.2	上海大学通信与信息工程学院，副教授
2017.10 - 2017.11	英国爱丁堡大学(The University of Edinburgh)医学院，访问学者
2010.7 - 2013.2	上海大学通信与信息工程学院，讲师

发表论文：

研究兴趣：医学信号与图像处理、计算机视觉、智能医疗、计算机辅助诊断与疗效评估

代表性论文详见后文英文介绍“Selected Publications”

主持项目：

主持国家自然科学基金面上项目，依托跨领域跨组织器官迁移学习的跟腱损伤超声诊断与预后预测

主持国家自然科学基金国际合作与交流项目，脑疾病研究中人脑突触图像分析的深度学习技术

主持国家自然科学基金面上项目，融合颈部淋巴结血流、弹性与结构信息的多模态超声诊断与疗效评估

主持国家自然科学基金青年项目，斑块血流灌注时空异质性的高造影组织比超声造影成像

主持中国计算机学会(CCF)-百度松果基金，Paddle Ultrasound —— 面向医学超声影像的乳腺癌智能诊断系统

主持上海市自然科学基金，基于声辐射力脉冲成像与计算机图像分析的斑块易损性评价

主持上海市教委上海高校青年教师培养资助计划项目，动脉粥样硬化斑块的超声造影图像分割

主持复旦大学附属华山医院横向项目，基于超声影像组学与深度学习的数据分析与处理

主持同济大学附属东方医院横向项目，基于U-Net与逐点门控深度网络的左心室肥厚智能诊断

学术任职：

学术委员：上海市医疗图像与医学知识图谱人工智能重点实验室学术委员会委员，中国仪器仪表学会青年委员会委员，中国生物医学工程学会青年委员会委员，中国自动化学会智能传感与检测专委会委员，上海市医学会超声医学专委会人工智能学组副组长

获奖与荣誉：

2023.2	2022年度湖北省科技进步二等奖
2022.11	上海市高层次人才
2018.10	中国仪器仪表学会第20届青年学术会议优秀论文
2013.6	上海大学青年教师课堂教学竞赛理工科组第四名
2011.6	上海市人才计划“晨光计划”

Professional Experience：

Mar. 2020 – Present	Professor, Institute of Biomedical Engineering, Shanghai University, Shanghai, China
Mar. 2013 – Feb. 2020	Associate Professor, Institute of Biomedical Engineering, Shanghai University, Shanghai, China
Oct. 2017 - Nov. 2017	Visiting Scholar, Edinburgh Medical School, The University of Edinburgh, UK
Jul. 2010 - Feb. 2013	Lecturer, Institute of Biomedical Engineering, Shanghai University, Shanghai, China

Education：

Sep. 2005 - Jul. 2010

Ph.D., Department of Electronic Engineering, Fudan University, Shanghai, China.

Supervisor: Professor Yuanyuan Wang

Aug. 2008 - Aug. 2009

Visiting Ph.D. Student, Department of Biomedical Engineering, Duke University, Durham, NC, USA.

Supervisor: Professor Morton Friedman

Sep. 2001 - Jul. 2005

B.S., Department of Electronic Engineering, Fudan University, Shanghai, China.

Research Interests：

Biomedical signal and image processing, computer vision, intelligent medicine, computer aided diagnosis and therapeutic effect evaluation.

Selected Publications：

#Equal contribution; *Corresponding authors

1. Haobo Chen#, Yehua Cai#, Changyan Wang, Lin Chen, Bo Zhang, Hong Han, Yuqing Guo, Hong Ding*, Qi Zhang*. Multi-Organ Foundation Model for Universal Ultrasound Image Segmentation with Task Prompt and Anatomical Prior. IEEE Transactions on Medical Imaging. 2024, Early Access, https://doi.org/10.1109/TMI.2024.3472672.

2. Weiwei Jiao#, Hong Han#, Yehua Cai#, Haihao He, Haobo Chen, Hong Ding, Wenping Wang, Qi Zhang*. Cross-modality segmentation of ultrasound image with generative adversarial network and dual normalization network. Pattern Recognition, 2025, 157, 110953

3. Changyan Wang, Haobo Chen, Xin Zhou, Meng Wang, Qi Zhang*. SAM-IE: SAM-based image enhancement for facilitating medical image diagnosis with segmentation foundation model. Expert Systems with Applications, 2024, 249, 123795.

4. Yifei Yan#; Rongzong Liu#; Haobo Chen; Limin Zhang*; Qi Zhang*. CCT-Unet: A U-Shaped Network Based on Convolution Coupled Transformer for Segmentation of Peripheral and Transition Zones in Prostate MRI. IEEE Journal of Biomedical and Health Informatics, 2023, 27(9), 4341 – 4351.

5. Haihao He#, Yuhan Liu#, Xin Zhou, Jia Zhan, Changyan Wang, Yiwen Shen, Haobo Chen, Lin Chen*, Qi Zhang*. Can incorporating image resolution into neural networks improve kidney tumor classification performance in ultrasound images? Medical & Biological Engineering & Computing, 2024, https://doi.org/10.1007/s11517-024-03188-8

6. Weibin Zhang#, Qihui Guo#, Yuli Zhu, Meng Wang, Tong Zhang, Guangwen Cheng, Qi Zhang*, Hong Ding*. Cross-institutional evaluation of deep learning and radiomics models in predicting microvascular invasion in hepatocellular carcinoma: validity, robustness, and ultrasound modality efficacy comparison. Cancer Imaging, 2024, 24, 142.

7. Changchun Li#, Yan Liu#, Rui Dong, Tianjie Zhang, Ye Song*, Qi Zhang*. Deep learning radiomics on shear wave elastography and b-mode ultrasound videos of diaphragm for weaning outcome prediction. Medical Engineering & Physics, 2024, 123, 104090.

8. Jieyi Liu, Changchun Li, Liping Liu, Haobo Chen, Hong Han, Bo Zhang*, Qi Zhang*. Speckle noise reduction for medical ultrasound images based on cycle-consistent generative adversarial network. Biomedical Signal Processing and Control, 2023, 86, 105150(1-10)

9. Zhou Xu#, Fei Yu#, Bo Zhang*, Qi Zhang*. Intelligent diagnosis of left ventricular hypertrophy using transthoracic echocardiography videos. Computer Methods and Programs in Biomedicine, 2022, 226, 107182(1-11).

10. Zhou Xu#, Yuqun Wang#, Man Chen*, Qi Zhang*. Multi-region radiomics for artificially intelligent diagnosis of breast cancer using multimodal ultrasound. Computers in Biology and Medicine, 2022, 149, 105920(1-8).

11. Zhou Xu#, Fei Yu#, Bo Zhang*, Qi Zhang*. Intelligent diagnosis of left ventricular hypertrophy using transthoracic echocardiography videos. Computer Methods and Programs in Biomedicine, 2022, 226, 107182(1-11).

12. Fengjun Liu#, Qi Zhang#, Chao Huang#, Chunzi Shi#, Lin Wang#, Nannan Shi, et al. CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients. Theranostics, 2020; 10(12): 5613-5622. (ESI Highly Cited)

13. Yuqun Wang#, Zhou Xu#, Lei Tang, Qi Zhang+, Man Chen+. The Clinical Application of Artificial Intelligence Assisted Contrast Enhanced Ultrasound on BI-RADS Category 4 Breast Lesions. Academic Radiology, 2023, 30 (S2), S104-S113.

14. Qiuyue Liao^#, Qi Zhang^#, Xue Feng^#, Haibo Huang^#, Haohao Xu^#, Baoyuan Tian, Jihao Liu, Qihui Yu, Na Guo, Qun Liu, Bo Huang, Ding Ma, Jihui Ai*, Shugong Xu*, Kezhen Li*. Development of deep learning algorithms for predicting blastocyst formation and quality by time-lapse monitoring. Communications Biology, 2021, 4:415(1-9).

15. Haobo Chen, Haohao Xu, Peng Shi, Yuchen Gong, Zhen Qiu, Lei Shi*, Qi Zhang*. 3-D Gabor-based anisotropic diffusion for speckle noise suppression in dynamic ultrasound images. Physical and Engineering Sciences in Medicine, 2021, 44: 207–219.

16. Nannan Shi, Fengxiang Song, Fengjun Liu, Pengrui Song, Yang Lu, Qinguo Hou, Xinyan Hua, Yun Ling, Jiulong Zhang, Chao Huang, Lei Shi, Zhiyong Zhang, Fei Shan, Qi Zhang*, Yuxin Shi*. Preliminary investigation of relationship between clinical indicators and CT manifestation patterns of COVID-19 pneumonia improvement. Journal of Thoracic Disease, 2020, 12(10):5896-5905.

17. Qi Zhang*, Shuang Song, Yang Xiao*, et al. Dual-mode artificially-intelligent diagnosis of breast tumours in shear-wave elastography and B-mode ultrasound using deep polynomial networks. Medical Engineering & Physics, 2019, 64, 1-6.

18. Haohao Xu, Yuchen Gong, Xinyi Xia, Dong Li, Zhuangzhi Yan, Jun Shi, and Qi Zhang*. Gabor-based anisotropic diffusion with lattice Boltzmann method for medical ultrasound despeckling. Mathematical Biosciences and Engineering, 2019, 16, 7546–7561.

19. Qi Zhang*, Shuang Song, Yang Xiao*, Shuai Chen, Jun Shi, Hairong Zheng. Dual-mode artificially-intelligent diagnosis of breast tumours in shear-wave elastography and B-mode ultrasound using deep polynomial networks. Medical Engineering & Physics, 2019, 64, 1-6.

20. Qi Zhang*, Jingyu Xiong, Yehua Cai, Jun Shi, Shugong Xu, Bo Zhang*. Multimodal feature learning and fusion on B-mode ultrasonography and sonoelastography using point-wise gated deep networks for prostate cancer diagnosis. Biomedical Engineering-Biomedizinische Technik, 2020, 65(1): 87–98.

21. Jun Shi, Zeyu Xue, Yakang Dai, Bo Peng, Yun Dong, Qi Zhang, Yingchun Zhang. Cascaded multi-column RVFL+ classifier for single-modal neuroimaging-based diagnosis of Parkinson’s disease. IEEE Transactions on Biomedical Engineering, 2019, 66, 2362 – 2371.

22. Jun Shi, Zheng Li, Shihui Ying, Chaofeng Wang, Qi Zhang, Pingkun Yan. MR image super-resolution via wide residual networks with fixed skip connection. IEEE Journal of Biomedical and Health Informatics. 2019, 23, 1129 - 1140.

23. Jun Shi, Xiao Zheng, Jinjie Wu, Yan Li, Qi Zhang, Shihui Ying. Quaternion Grassmann average network for learning representation of histopathological image. Pattern Recognition. 2019, 89: 67-76.

24. Yechen Zhu, Yangchuan Liu, Qi Zhang, Cishen Zhang∗, and Xin Gao∗. A fast iteration approach to undersampled cone-beam CT reconstruction. Journal of X-Ray Science and Technology, 2019, 27(1), 111-129.

25. Jun Shi, Xiao Zheng, Yan Li, Qi Zhang, Shihui Ying. Multimodal neuroimaging feature learning with multimodal stacked deep polynomial networks for diagnosis of Alzheimer's disease. IEEE Journal of Biomedical and Health Informatics. 2018, 22(1): 173-183.

26. Bangming Gong, Jun Shi*, Shihui Ying, Yakang Dai, Qi Zhang, Yun Dong, Hedi An, Yingchun Zhang. Neuroimaging-based diagnosis of Parkinson’s disease with deep neural mapping large margin distribution machine. Neurocomputing. 2018, 320: 141-149.

27. Jun Shi, Qingping Liu, Chaofeng Wang, Qi Zhang, Shihui Ying, Haoyu Xu. Super-resolution reconstruction of MR image with a novel residual learning network Algorithm. Physics in Medicine & Biology. 2018, 63(8):085011.

28. Qi Zhang*, Jingfeng Suo, Wanying Chang, Jun Shi, Man Chen*. Dual-modal computer-assisted evaluation of axillary lymph node metastasis in breast cancer patients on both real-time elastography and B-mode ultrasound. European Journal of Radiology, 2017, 95, 66–74.

29. Qi Zhang*, Yang Xiao, Jingfeng Suo, Jun Shi, Jinhua Yu, Yi Guo, Yuanyuan Wang, Hairong Zheng. Sonoelastomics for Breast Tumor Classification: A Radiomics Approach with Clustering-Based Feature Selection on Sonoelastography. Ultrasound in Medicine and Biology. 2017, 43(5), 1058-1069.

30. Qi Zhang*, Jing Yao, Yehua Cai, Limin Zhang, Yishuo Wu, Jingyu Xiong, Jun Shi, Yuanyuan Wang, Yi Wang. Elevated hardness of peripheral gland on real-time elastography is an independent marker for high-risk prostate cancers. Radiologia Medica, 2017, 122(12):944-951.

31. Qi Zhang, Yehua Cai, Yinghui Hua, Jun Shi, Yuanyuan Wang, Yi Wang. Sonoelastography shows that Achilles tendons with insertional tendinopathy are harder than asymptomatic tendons. Knee Surgery, Sports Traumatology, Arthroscopy. 2017, 25, 1839–1848.

32. Qi Zhang*, Congcong Yuan, Wei Dai, Lei Tang, Jun Shi, Zuoyong Li, Man Chen*. Evaluating pathologic response of breast cancer to neoadjuvant chemotherapy with computer-extracted features from contrast-enhanced ultrasound videos. Physica Medica, 2017, 39, 156–163.

33. Huaipeng Dong, Qi Zhang*, Jun Shi. Intensity Inhomogeneity Compensation and Tissue Segmentation for Magnetic Resonance Imaging with Noise-Suppressed Multiplicative Intrinsic Component Optimization. Optical Engineering, 2017, 56(12), 123103(1-12).

34. Jun Shi, Jinjie Wu, Yan Li, Qi Zhang, Shihui Ying*. Histopathological Image Classification with Color Pattern Random Binary Hashing Based PCANet and Matrix-Form Classifier. IEEE Journal of Biomedical and Health Informatics. 2017, 21 (5): 1327-1337.

35. Zeju Li, Yuanyuan Wang, Jinhua Yu, Yi Guo, Qi Zhang. Age groups related glioblastoma study based on radiomics approach. Computer Assisted Surgery, 2017, 22, S1, 18-25.

36. Junjie Zhang, Jie Yin, Qi Zhang, Jun Shi*, Yan Li. Robust sound event classification with bilinear multi-column ELM-AE and two-stage ensemble learning. EURASIP Journal on Audio, Speech, and Music Processing. 2017, 11.

37. Qi Zhang, Yang Xiao, Wei Dai, Jingfeng Suo, Congzhi Wang, Jun Shi, Hairong Zheng. Deep learning based classification of breast tumors with shear-wave elastography. Ultrasonics, 2016, 72, 150-157.

38. Jun Shi, Shichong Zhou, Xiao Liu, Qi Zhang, Minhua Lu, Tianfu Wang. Stacked deep polynomial network based representation learning for tumor classification with small ultrasound image dataset. Neurocomputing, 2016, 194, 87 –94.

39. Qi Zhang, Chaolun Li, Hong Han, Wei Dai, Jun Shi, Yuanyuan Wang, Wenping Wang: Spatio-temporal quantification of carotid plaque neovascularization on contrast enhanced ultrasound: Correlation with visual grading and histopathology. European Journal of Vascular and Endovascular Surgery, 2015, 50, 289-296.

Professional Societies：

Shanghai Key Laboratory of Artificial Intelligence for Medical Image and Knowledge Graph (Academic Committee)

Chinese Association for Biomedical Engineering (Youth Committee)

Chinese Association for Scientific Instrument (Youth Committee)

Shanghai Society of Biomedical Engineers (Ultrasonic Medical Engineering Committee)

Chinese Association for Ultrasonic Medical Engineering (member)

Chinese Society of Biomedical Engineers (member)