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讲师
  • 姓名:郑强

  • 职务:

  • 职称:讲师    

  • 所在院系:计算机系

  • 最后学位:博士

  • 最后学历:

  • 最后毕业院校:山东大学

  • 所学专业:通信与信息系统

  •  

  • 研究方向:Biomedical image analysis (BioMedIA)

  • 联系方式:zhengqiang@ytu.edu.cn

个人简介

◆ Aug. 2018 - Present, Postdoctor Researcher, Children's Hospital of Philadelphia and University of Pennsylvania, United States. Advisor: Raymond Sze, Hao Huang, Minsun Hwang

◆ Jan. 2017 - Aug. 2018, Postdoctor Researcher, Perelman School of Medicine, University of Pennsylvania, United States. Advisor: Yong Fan

◆ Aug. 2015 - Dec. 2016, Postdoctor Researcher, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China. Advisor: Yong Fan, Ming Tang

◆ Sep. 2008 - Dec. 2013, Ph.D., Communication and Information System, School of Information Engineering, Shandong University, China. Advisor: Enqing Dong

Sep. 2004 - June 2008, B.Sc., Electronic Information Science and Technology, School of Information Engineering, Shandong University, China

Research Interests:

image segmentation, disease diagnosis, outcome prediction, feature selection

level set, graph theory, multi-atlas, machine learning, deep learning


主讲课程:


主要科研成果

Projects: 
◆ Project 1: Liver tumor benign/malignant diagnosis and therapy recommendation based on pathology and histology analysis

   ◆ Project 2: Arterial spin labeling (ASL) data analysis for brain injury analysis based on cerebral blood flow calculation

   ◆ Project 3: fMRU, MAG 3, and US data analysis for surgical intervention prediction with ureteropelvic junction obstruction (UPJO)

   ◆ Project 4: automatic leg length measurement software development for Radiologist clinical report

   ◆ Project 5: Diagnosis of congenital abnormalities of the kidney and urinary tract in children based on ultrasound imaging and transfer learning 
◆ Project 6: MR brain segmentation based on semi-supervised and supervised learning methods including deep learning, multi-atlas method, label propagation algorithm

    ◆ Project 7: Quantification of chest lymphatic flow patterns for lymphatic circulation disorder diagnosis using dynamic contrast magnetic resonance lymphangiogram

   ◆ Project 8: Echocardiography-derived strain features identification for predicting the left ventrical ejecation fraction decline that related to the Doxorubicin cardiotoxicity using lasso-based multi-instance learning in the longitudinal study of therapy for breast cancer patients
◆ Project 9: Aorta segmentation for cardiac disease analysis based on CT chest images and level set methods
◆ Project 10: Hypertension and hypertension/depression analysis based on machine learning methods including classification and feature selection


 

Publications (Selected)

[1] Qiang Zheng, Juan S. Martin-Saavedra, Minhui Ouyang, Sandra Saade-Lemus, Qinlin Yu, Hao Huang, Raymond Sze, Misun Hwang, "Quantitative ASL perfusion method for detection of neonatal hypoxic ischemic injury as reference standard for developing contrast-enhanced ultrasound," The Society of Pediatric Radiology (SPR) 2019 Annual Meeting, Apr 30-May 4, Oral.

[2] Qiang Zheng, Juan S. Martin-Saavedra, Minhui Ouyang, Sandra Saade-Lemus, Qinlin Yu, Hao Huang, Raymond Sze, Misun Hwang, "Region-specific perfusion alterations in neonatal hypoxic ischemic injury evaluated with arterial spin labeling MRI," The Society of Pediatric Radiology (SPR) 2019 Annual Meeting, Apr 30-May 4, Oral.

[3] Qiang Zheng, Susan Furth, Gregory Tasian, Yong Fan, "Computer aided diagnosis of congenital abnormalities of the kidney and urinary tract in children based on ultrasound imaging data by integrating texture image features and deeptransfer learning image features", Journal of Pediatric Urology, Mar 2018, in press. (SCI)

[4] Qiang Zheng, Yihong Wu, Yong Fan, "Integrating semi-supervised and supervised learning methods for label fusion in multi-atlas based image segmentation", frontiers in neuroinformatics, vol. 12, no. 69, pp. 1-11, Oct 2018. (SCI)

    (We develop a multi-atlas based image segmentation toolbox with code package release @NITRC with link https://www.nitrc.org/frs/?group_id=1242)

[5] Henry CHeng, Qiang Zheng, Xiaofeng Zhu, ..., Yong Fan, Bonnie Ky, "The use of machine learning for predict Doxorubicin cardiotoxicity, " vol.71, no. 11, Journal of the American College of Cardiology, vol.71, no. 11, Mar 2018. (SCI)

[6] Qiang Zheng, Honglun Li, Baode Fan, Shuanhu Wu, Jindong Xu, “Integrating support vector machine and graph cuts for medical image segmentation,” Journal of Visual Communication and Image Representation, vol. 55, pp. 157-165, Aug 2018. (SCI)

[7] Qiang Zheng, Yong Fan, "Integrating semi-supervised label propagation and random forests for multi-atlas based hippocampus segmentation," IEEE 15th International Symposium on Biomedical Imaging (ISBI), pp. 154-157,  Washington DC, USA, Apr 4-7, 2018. (EI)

[8] Qiang Zheng, Gregory Tasian, Yong Fan, "Transfer learning for diagnosis of congenital abnormalities of the kidney and urinary tract in children based on ultrasound imaging," IEEE 15th International Symposium on Biomedical Imaging (ISBI), pp. 1487-1490,  Washington DC, USA, Apr 4-7, 2018. (EI)

[9] Qiang Zheng, Steven Warner, Gregory Tasian, Yong Fan, "A dynamic graph-cuts method with integrated multiple feature maps for segmenting kidneys in ultrasound images," Academic Radiology, vol. 25, no. 9, pp. 1136-1145, Sep 2018. (SCI)

[10] Qiang Zheng, Honglun Li, Baode Fan, Shuanhu Wu, Jindong Xu, Zhulou Cao, “Modified localized multiplicative graph cuts based active contour model for object segmentation based on dynamic narrow band scheme,”Biomedical Signal Processing and Control, vol. 33, pp. 119-131, Mar, 2017. (SCI)

[11] Qiang Zheng, Honglun Li, Baode Fan, Shuanhu Wu, Jindong Xu, “Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images,” Optical Review, vol.24, no. 6, pp. 653-659, Dec 2017. (SCI)

[12] Qiang Zheng, BaoDe Fan, ShuanHu Wu, and JinDong Xu, “Novel local-region-based active contour integrating fuzzy clustering and structure constraint for putamen segmentation in T1-weighted magnetic resonance brain images,” Journal of Medical Imaging and Health informatics, vol.7, pp. 956-961, Sep 2017. (SCI)

[13] 孙文燕,董恩清,曹祝楼,郑强,“一种基于模糊主动轮廓模型的鲁棒局部分割方法,”自动化学报,vol. 43, no. 4, pp. 611-621, Apr 2017。(EI)

[14] Zhulou Cao, Enqing Dong, Qiang Zheng, Wenyan Sun, Zhenzhi Li, “Accurate inverse-consistent symmetric optical flow for 4D CT lung egistration,”Biomedical Signal Processing and Control, vol. 24, pp. 25-33, Feb 2016. (SCI)

[15] Jindong Xu, Mengying Ni, Yanjie Zhang, Xiangrong Tong, Qiang Zheng, Jinglei Liu, “Remote sensing image fusion method based on multiscale morphological,” Journal of Applied Remote Sensing, vol. 10, no. 2, pp. 025018, Jun 2016. (SCI)

[16] 潘景昌,罗阿理,韦鹏,姜斌,李荫碧,郑强,“基于多分辨率融合距离的低质量星系光谱红移测量方法,”光谱学与光谱分析,vol. 36, no. 5, pp. 1521-1525, May 2016。(SCI)

[17] 潘景昌,王杰,姜斌,罗阿理,韦鹏,郑强,“一种基于Map/Reduce分布式计算的恒星光谱分类方法,”光谱学与光谱分析,vol. 36, no. 5, pp. 1521-1525, Aug 2016。(SCI)

[18] Qiang Zheng, Enqing Dong, Zhulou Cao, and Wenyan Sun, “Active contour model driven by linear speed function for local segmentation with robust initialization and application in MR brain Images,” Signal Processing, vol. 97, pp. 117-133, Apr 2014. (SCI)

[19] Enqing Dong, Qiang Zheng*, Wenyan Sun, Zhenguo Li, and Li Li,“Constrained Multiplicative graph cuts based active contour model for magnetic resonance brain image series segmentation,” Signal Processing, vol. 104, pp. 59-69, Nov 2014. (SCI)

[20] Qiang Zheng, Enqing Dong, Zhulou Cao, Wenyan Sun, and Zhenguo Li, “Modified localized graph cuts based active contour model for local segmentation with surrounding nearby clutter and intensity inhomogeneity,” Signal Processing, vol. 93, no. 4, pp. 961-966, Apr 2013. (SCI)

[21] 郑强,董恩清,“窄带主动轮廓模型及在医学和纹理图像局部分割中的应用,”自动化学报,vol. 39, no. 1, pp. 21-30, Jan 2013。(EI)

[20] Qiang Zheng, Enqing Dong, and Zhulou Cao, “Graph cuts based active contour model with selective local or global segmentation,” Electronics Letters, vol. 48, no. 9, pp. 490-491, Apr 2012. (SCI)

[22] Qiang Zheng, Enqing Dong, “New local segmentation model for images with intensity inhomogeneity,” Optical Engineering, vol. 51, no. 3, pp. 037006-1-037006-10, Apr 2012. (SCI)

[23] 郑强,董恩清,“一种新的基于二值水平集和形态学的局部分割方法,”电子与信息学报,vol. 34,no. 2,pp. 375-381,Apr 2012。(EI)



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