张麒

学历: 博士研究生

职称: 教授

学科专长: 智能医疗、医学图像处理、机器学习

所属学科方向(团队): 生物医学工程

办公室: T803

联系电话:66137256  

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

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、智能医疗、计算机辅助诊断与疗效评估、医学超声工程

截至20216月,共发表100多篇论文,SCI论文50篇,详见后文英文介绍“Selected Publications

主持与参与项目  

主持国家自然科学基金面上项目(No. 62071285)

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(No. 6181101584)

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(No. 61671281)

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(No. 61401267)

斑块血流灌注时空异质性的高造影组织比超声造影成像

主持上海市自然科学基金(No. 12ZR1444100)

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“晨光计划”项目(No. 11CG45)

超声造影图像中动脉粥样硬化斑块的特征提取

主持上海市教委上海高校青年教师培养资助计划项目(No. shu11047)

动脉粥样硬化斑块的超声造影图像分割

主持上海高校教师产学研践习计划

践习单位:上海医疗器械股份有限公司

主持上海大学创新基金(No. 10010710007)

基于格子波尔兹曼模型的动脉磁共振图像处理与流场分析

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

主持福建省信息处理与智能控制重点实验室开放项目(No. MJUKF201713)

基于逐点门控深度网络的淋巴结超声造影计算机辅助诊断

主持同济大学附属东方医院横向项目  

基于细胞形态学分析的数据处理系统

主持上海交通大学医学院附属同仁医院横向项目  

超声影像组学数据分析与处理系统

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,中国生物医学工程学会青年委员会委员,中国仪器仪表学会青年委员会委员,中国医学装备协会超声分会远程及移动超声专委会委员,上海市生物医学工程学会超声专委会委员

杂志编委:Journal of Biomedical Engineering and Informatics; Advanced   Ultrasound in Diagnosis and Therapy

审 稿 人:IEEE Transactions on Medical Imaging;IEEE Transactions on Biomedical Engineering;IEEE Journal of Biomedical and Health Informatics;European Journal of Radiology;Ultrasound   in Medicine and Biology; Ultrasonics; Medical Physics

项目评审:国家自然科学基金面上项目、青年项目函评专家

获奖情况  

2018.10 中国仪器仪表学会第20届青年学术会议优秀论文

2015.9 中国仪器仪表学会第17届青年学术会议优秀论文

2014.9 上海康复技术与产品创新大赛优胜奖

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”(晨光学者)

指导研究生  

当前:黄海博、陈浩波、董玉彩、严逸飞、陈瀛、徐舟

已毕业:

杨利静;黄春春、唐金良、陈帅、姜西源、戴伟、周茉莉、施鹏、索静峰、廖宇、胡妍璐、董怀鹏、林细林、刘跃、张德龙、熊竞宇、石颉、宋爽、朱叶晨、许浩浩、余其徽、田宝园

毕业生去向:华为,平安科技,联影,中国移动,浦发银行,宁德时代等

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

Jun. 2007 - Sep. 2007  Research Intern, Philips Research East Asia (now Philips   Research Asia - Shanghai), 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 aided diagnosis and therapeutic effect evaluation,   and medical ultrasonics such as sonoelastography and contrast-enhanced   ultrasound.

Selected   Publications  

Journal Publications:

1. 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. ((#Equal contribution; ESI   Highly Cited)

2. Haibo   Huang, Haobo Chen, Haohao Xu, Ying Chen, Qihui Yu, Yehua Cai*, Qi   Zhang*. Cross-Tissue/Organ Transfer Learning for Segmentation of Ultrasound   Images using Deep Residual U-Net. Journal of Medical and Biological   Engineering, 2021, 41: 137–145

3. 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.

4. Fei Yu, Haibo   Huang, Qihui Yu, Yuqing Ma, Qi   Zhang*, Bo Zhang*. Artificial intelligence-based myocardial texture   analysis in etiological differentiation of left ventricular hypertrophy. Annals   of Translational Medicine, 2021, 9(2):108(1-9).

5. Nannan Shi, Chao   Huang, Qi Zhang*, Chunzi Shi,   Fengjun Liu, et al. Longitudinal trajectories of pneumonia lesions and   lymphocyte counts associated with disease severity among convalescent   COVID-19 patients: a group-based multi-trajectory analysis. BMC Pulmonary Medicine, 2021, accepted.

6. 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 and Validation of a Deep Learning   Algorithm for Predicting Blastocyst Formation by Time-lapse Monitoring. Communications   Biology, 2021, accepted.

7. Hai-xia Yuan#,   Qi-hui Yu#, Yan-qun Zhang, Qing Yu, Qi   Zhang*, Wen-Ping Wang*. Ultrasound radiomics for preoperative identification of gallbladder true-and pseudo-polyps based on   spatial and morphological features. Frontiers in Oncology, 2020, 10:1719(1-10).

8. Ying Chen#, Jianwei Jiang#, Jie Shi, Wanying Chang, Jun Shi,   Man Chen*, Qi Zhang*.   Dual-mode ultrasound radiomics and intrinsic imaging phenotypes for diagnosis of lymph node   lesions. Annals of Translational Medicine, 2020, 8(12): 742(1-15).

9. 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.

10. 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.

11. 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.

12. Ying Chen,   Xiaomin Qin, Jingyu Xiong, Shugong Xu, Jun Shi, Huabing Lv, Lin Li, Hui Xing, Qi Zhang. Deep Transfer   Learning for Histopathological Diagnosis of Cervical Cancer Using   Convolutional Neural Networks with Visualization Schemes. Journal of Medical   Imaging and Health Informatics, 2020, 10, 391-400.

13. 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.

14. 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.

15. 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.

16. 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.

17. 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.

18. 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.

19. Qianru Li#, Qi Zhang#, Yehua Cai, Yinghui   Hua*. Patients with Achilles tendon rupture have a degenerated contralateral Achilles   tendon: an elastography study. BioMed Research   International, 2018, 2367615. (#Equal contribution)

20. Qi Zhang, Yue Liu, Hong   Han*, Jun Shi, Wenping Wang*. Artificial intelligence based diagnosis for   cervical lymph node malignancy using the point-wise gated Boltzmann machine. IEEE   Access, 2018, 6(1), 60605 - 60612.

21. 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.

22. 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.

23. 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.

24. Lehang Guo, Dan   Wang, Yiyi Qian, Xiao Zheng, Chongke Zhao, Xiaolong Li, Xiaowan Bo, Wenwen   Yue, Qi Zhang, Jun   Shi*, Huixiong Xu. A two-stage multi-view learning framework based   computer-aided diagnosis of liver tumors with contrast enhanced ultrasound   images. Clinical Hemorheology and Microcirculation. 2018, 69(3):   343-354.

25. Yurong Huang, Shuying   Li, Jinhua Yu, Yuanyuan Wang, Qi   Zhang. Simplified Ultrasound Contrast Agent   Microbubble Modeling with Bubbles Interaction. Journal of Medical Imaging and Health   Informatics, 2018, 8(7), 1428-1435.

26. Jun Shi, Yiyi   Qian, Jinjie Wu, Shichong Zhou*, Yehua Cai*, Qi Zhang, Xiaoxing Feng, Cai Chang. Ultrasound Image   Based Tumor Classification via Deep Polynomial Network and Multiple Kernel   Learning. Current Medical Imaging Reviews, 2018, 14(2),   301-308.

27. 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.

28. 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.

29. 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.

30. 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.

31. 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.

32. 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).

33. 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.

34. Yurong Huang,   Jinhua Yu*, Yusheng Tong, Shuying Li, Liang Chen*, Yuanyuan Wang, Qi Zhang. Contrast-Enhanced   Ultrasound Imaging Based on Bubble Region Detection. Applied   Sciences, 2017, 7(10), 1098.

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, 8794.

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.

40. Qi Zhang, Yang Xiao, Shuai Chen, Congzhi Wang, Hairong   Zheng: Quantification of elastic heterogeneity using contourlet-based texture   analysis in shear-wave elastography for breast tumor classification.   Ultrasound in Medicine and Biology, 2015, 41(2), 588-600.

41. Qi Zhang, Chaolun Li, Moli Zhou, Yu Liao, Chunchun Huang,   Jun Shi, Yuanyuan Wang, Wenping Wang: Quantification of carotid plaque   elasticity and intraplaque neovascularization using contrast-enhanced   ultrasound and image registration-based elastography. Ultrasonics, 2015, 62,   253–262.

42. Jun Shi, Xiao   Liu, Yan Li, Qi Zhang,   Yingjie Li, Shihui Ying: Multi-channel EEG based sleep stage classification   with joint collaborative representation and multiple kernel learning. Journal   of Neuroscience Methods, 2015, 354, 94–101.

43. Jun Shi, Qikun   Jiang, Qi Zhang, Qinghua   Huang, Xuelong Li: Sparse kernel entropy component analysis for   dimensionality reduction of biomedical data. Neurocomputing, 2015, 168,   930–940.

44. Qi Zhang, C. Li, H. Han, L. Yang, Y. Wang, W. Wang:   Computer-aided quantification of contrast agent spatial distribution within   atherosclerotic plaque in contrast-enhanced ultrasound image sequences,   Biomedical Signal Processing and Control, 2014, 13, 50-61.

45. Qi Zhang, Hong Han, Chunhong Ji, Jinhua Yu, Yuanyuan Wang,   Wenping Wang: Gabor-based anisotropic diffusion for speckle noise reduction   in medical ultrasonography, Journal of the Optical Society of America A,   2014, 31(6), 1273-1283.

46. Qi Zhang, D. Steinman, M. Friedman: Use of factor analysis   to characterize arterial geometry and predict hemodynamic risk: application   to the human carotid bifurcation, Journal of Biomechanical Engineering -   ASME, 2010, 132(11): 114505 (1-5).

47. Qi Zhang, Y. Wang, W. Wang, et al: Automatic segmentation   of calcifications in intravascular ultrasound images using snakes and the   contourlet transform, Ultrasound in Medicine and Biology, 2010, 36(1):   111-129.

Conference Proceedings and Abstracts:

48. Haohao Xu,   Zhuangwei Xu, Wenting Gu, Qi Zhang*. A Two-Stage Fully Automatic Segmentation   Scheme Using Both 2D and 3D U-Net for Multi-sequence Cardiac MR. In: Pop M.   et al. (eds) Statistical Atlases and Computational Models of the Heart.   Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification   Challenges, MICCAI Challenges 2019 (also STACOM 2019). Lecture Notes in   Computer Science, vol 12009. Springer, Cham, 2020, 309-316.

49. Haohao Xu, Qi   Zhang*, Huaipeng Dong, Xiyuan Jiang, Jun Shi. Speckle Suppression of   Ultrasonography Using Maximum Likelihood Estimation and Weighted Nuclear Norm   Minimization. The 40th Annual International Conference of the IEEE   Engineering in Medicine and Biology Society (EMBS). July 2018, Honolulu, USA.

50. Jun Shi, Minjun   Yan, Yun Dong, Xiao Zheng, Qi Zhang, Hedi An. Multiple kernel learning based   classification of Parkinson’s disease with multi-modal transcranial   sonography. The 40th Annual International Conference of the IEEE Engineering   in Medicine and Biology Society (EMBS). July 2018, Honolulu, USA.

51. Xiao Zheng, Jun   Shi, Yan Li, Xiao Liu, Qi Zhang. Multi-modality stacked deep polynomial   network based feature learning for Alzheimer’s disease diagnosis. 2016 IEEE   International Symposium on Biomedical Imaging (ISBI). April 2016, Prague,   Czech, 851 - 854.

52. Jinjie Wu, Jun   Shi, Yan Li, Jingfeng Suo, Qi Zhang. Histopathological image classification   using random binary hashing based PCANet and bilinear classifier. The 2016   European Signal Processing Conference (EUSIPCO), Aug. 2016, Budapest, Hungary, 2050-2054.

53. Congcong Yuan,   Lei Tang, Qi Zhang, Wanru Jia, Man Chen. Contrast-enhanced ultrasound for   evaluating the response of breast cancer to neoadjuvant chemotherapy:   Time-intensity curve analysis and texture analysis. The European Society for   Medical Oncology (ESMO) Annual Congress, Oct. 2016, Copenhagen, Denmark.

54. Xiao Liu, Jun   Shi, Qi Zhang: Tumor classification by deep polynomial network and multiple   kernel learning on small ultrasound image dataset. The 6th international   workshop on machine learning in medical imaging in the 18th International   Conference on Medical Image Computing and Computer Assisted Intervention   (MICCAI-MLMI), Oct. 2015, Munich, Germany. 313-320.

55. Qi Zhang,   Xiyuan Jiang, Wei Dai, Haiwu Zhao, Chunying Xu: Speckle suppression of   ultrasonic images using non-local means and McIlhagga-based anisotropic   diffusion, 2014 7th International Congress on Image and Signal Processing,   Oct. 2014, Dalian, China, 242-247.

56. Qi Zhang, Moli Zhou, Yun Dong, Ming Qian, Ming Chen: Detection of blood flow in left ventricle by   echocardiography using speckle image velocimetry, 2014 7th International   Congress on Image and Signal Processing, Oct. 2014, Dalian, China, 179-183.

57. Q. Zhang, L.   Yang, S. Chen: McIlhagga edge detector-based anisotropic diffusion for   speckle reduction of ultrasound images, 2013 IET/IEEE Second International   Conference on Smart and Sustainable City, August 2013, Shanghai, China,   437-441.

58. Q. Zhang, C.   Huang,, C. Li, et al: Ultrasound image segmentation based on multi-scale   fuzzy c-means and particle swarm optimization, 2012 IET International   Conference on Information Science and Control Engineering, Dec. 2012,   Shenzhen, China. 421-425.

59. Q. Zhang, L.   Yang, C. Li, and W. Wang: Contrast-enhanced ultrasound image segmentation of   atherosclerotic plaques using spatial-temporal analysis and snakes, the 2012   International Conference on Systems and Informatics, May 2012, Yantai, China.   1906-1910.

60. Q. Zhang, Y.   Wang,, J. Ma, and J. Shi: Contour Detection of Atherosclerotic Plaques in   IVUS Images Using Ellipse Template Matching and Particle Swarm Optimization, the   33rd Annual International Conference of the IEEE Engineering in Medicine and   Biology Society (EMBS), August 2011, Boston, MA, USA. 5174-5177.

61. J. Zhong, J.   Shi, Y. Cai, and Q. Zhang: Recognition of Hand Motions via Surface EMG Signal   with Rough Entropy, the 33rd Annual International Conference of the IEEE   Engineering in Medicine and Biology Society (EMBS), August 2011, Boston, MA,   USA. 4100-4103.

62. Q. Zhang, S.   Teo, Y. Wang, and M.H. Friedman: Computerized image analysis as a tool to   investigate the relationship between endothelial morphology and permeability,   the 22nd IEEE International Symposium on Computer-Based Medical Systems,   August 2009, Albuquerque, USA, 1-7.

63. Q. Zhang, D.   Steinman, M.H. Friedman: Prediction of disturbed flow by factor analysis of   carotid bifurcation geometry, Summer Bioengineering Conference, June 2009,   Lake Tahoe, USA, 1-2.

64. Q. Zhang, Y.   Wang, J. Yu, and S. Yang: Multimodal medical image registration using   geometric flow and Gabor filter, the IASTED International Conference on   Biomedical Engineering, February 2008, Innsbruck, Austria, 441-446.

65. Q. Zhang, Y.   Wang, W. Wang, et al: Discrimination of coronary microcirculatory dysfunction   based on generalized relevance LVQ, Lecture Notes in Computer Science, 2007,   4492: 1125-1132.

66. Q. Zhang, Y.   Wang, W. Wang, et al: Contour extraction from IVUS images based on GVF snakes   and wavelet transform, IEEE/ICME International Conference on Complex Medical   Engineering, May 2007, Beijing, China, 536-541.

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)

 

 

 
     

版权所有 © 上海大学   沪ICP备09014157   沪公网安备31009102000049号  地址:上海市宝山区上大路99号    邮编:200444   电话查询
 技术支持:上海大学信息化工作办公室   联系我们