Research Areas

Dr. Qin is currently the associate professor of the Institute of Biomedical and Health Engineering at Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences. Dr. Qin obtained his Ph.D. in Pattern Recognition and Intelligent System from the University of Chinese Academy of Sciences. During his doctoral study, he has studied at Stanford University as a visiting scholar in the United States to study medical physics. Dr. Qin has been engaged in the research of medical image reconstruction, image segmentation, and feature extraction for multi-modality medical imaging with machine learning and computer vision, which explores the new computing theories and methods of the learning-based algorithm in clinical diagnosis and treatment. Dr. Qin is a principal investigator or co-investigator on the National Key R& D Program of China, NSFC, Key R& D Program of Guangdong, and Key Natural Science Foundation of Shenzhen and projects from other funding agencies and corporates, and an author on more than 60 peer-reviewed publications (SCI/EI), an inventor or co-inventor on 37 issued and 80 pending patents. He has received numerous Innovation and Entrepreneurship Awards.  


Ø  2016.09-2017.09 Visiting Ph.D. Artificial Intelligence in Medicine, Stanford University, Palo Alto, CA, USA

Ø  2015.7-2019.07   Ph.D. in Pattern Recognition and Intelligent System, University of Chinese Academy of Sciences, Beijing, China

Ø  2009.9-2012.7    M.S. in Computer Application Technology, University of Chinese Academy of Sciences, Beijing, China

Ø  2005.9-2009.7    B.S. in Electronic Information Engineering, Shenyang Aerospace University, Liaoning Province, China


Ø  2018.11-present  Associate Professor in Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

Ø  2013.11-2018.10 Assistant Professor in Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

Ø  2012.6-2013.10   Research Assistant in Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China


Partial Published Journal Papers: 

1.      Zeng, G., He, J., & Qin, W(*). (2021). Wide-Field Pixel Super-Resolution Colour Lensfree Microscope for Digital Pathology. Frontiers in Oncology, Vol. 11, p. 4353.

2.      Yang Liu, Jiaxin Hou, Zhijun Zhu, Bingguang Liu, Manrui Cao(*), Wenjian Qin(*). Assessment of Breast Arteries and Lymph nodes by 3D MR Angiography Enhancement Imaging: Feasibility and Pilot Clinical Results, BMC Medical Imaging,2021, 21 (1), 1-10

3.      Zhang, Z., Yu, S., Qin, W., Liang, X., Xie, Y., & Cao, G. (2021). Self-supervised CT super-resolution with hybrid model. Computers in Biology and Medicine, 138.

4.      Zhao, W., Shen, L., Islam, M. T., Qin, W., Zhang, Z., Liang, X., … Li, X. (2021). Artificial intelligence in image-guided radiotherapy: a review of treatment target localization. Quantitative Imaging in Medicine and Surgery, 11(12).

5.      Chen, K., Qin, W., Xie, Y., & Zhou, S. (2021). Towards real time guide wire shape extraction in fluoroscopic sequences: A two phase deep learning scheme to extract sparse curvilinear structures. Computerized Medical Imaging and Graphics, 94.

6.      Song, L., Li, Y., Dong, G., Lambo, R., Qin, W., Wang, Y., Xie, Y. (2021). Artificial intelligence-based bone-enhanced magnetic resonance image—a computed tomography/magnetic resonance image composite image modality in nasopharyngeal carcinoma radiotherapy. Quantitative Imaging in Medicine and Surgery, 11(12).

7.      Xue, Y(#)., Qin, W.(#), Luo, C., Yang, P., Jiang, Y., Tsui, T., Niu, T.(*) (2021). Multi-Material Decomposition for Single Energy CT Using Material Sparsity Constraint. IEEE Transactions on Medical Imaging, 40(5), 1303–1318.

8.      Tian, Y., Xue, F., Lambo, R., He, J., An, C., Xie, Y., H Cao(*), Qin, W(*). (2020). Fully-automated functional region annotation of liver via a 2.5D class-aware deep neural network with spatial adaptation. Computer Methods and Programs in Biomedicine. 200, 105818.

9.      Qin, W., Wu, Y., Li, S., Chen, Y., Yang, Y., Liu, X., Hu, Z.(*) (2020). Automated segmentation of the left ventricle from MR cine imaging based on deep learning architecture. Biomedical Physics & Engineering Express, 6(2), 25009.

10.   He, Y., Qin, W., Wu, Y., Zhang, M., Yang, Y., Liu, X., Hu, Z. (2020). Automatic left ventricle segmentation from cardiac magnetic resonance images using a capsule network. Journal of X-Ray Science and Technology, (Preprint), 1–13.

11.   Zhang, Z., Liang, X., Qin, W., Yu, S., & Xie, Y. (2020). matFR: a matlab toolbox for feature ranking. Bioinformatics.

12.   Diao, S., Hou, J., Yu, H., Zhao, X., Sun, Y., Lambo, R. L., Qin, W(*) Luo, W. (2020). Computer-Aided Pathological Diagnosis of Nasopharyngeal Carcinoma Based on Deep Learning. The American Journal of Pathology. 190(8), 2020, PP, 1671-1700.

13.   Wen Li, Yafen Li, Wenjian Qin, Jianyang Xu, J. X. and Y. X. (2020). MRI Synthesis from Brain CT Images Based on Deep Learning Methods for MR-guided Radiotherapy. Quantitative Imaging in Medicine and Surgery.

14.   Yuan, Y., Qin, W., Ibragimov, B., Zhang, G., Han, B., Meng, M. Q.-H., & Xing, L. (2019). Densely Connected Neural Network With Unbalanced Discriminant and Category Sensitive Constraints for Polyp Recognition. IEEE Transactions on Automation Science and Engineering, PP, 1–10.

15.   Yuan, Y., Qin, W., Buyyounouski, M., Ibragimov, B., Hancock, S., Han, B., & Xing, L. (2019). Prostate cancer classification with multiparametric MRI transfer learning model. Medical Physics, 46(2), 756–765.

16.   Liang, X., Li, N., Zhang, Z., Yu, S., Qin, W., Li, Y., … Xie, Y. (2019). Shading correction for volumetric CT using deep convolutional neural network and adaptive filter. Quantitative Imaging in Medicine and Surgery, 9(7), 1242.

17.   Li, J., Igbe, T., Liu, Y., Nie, Z., Qin, W., Wang, L., & Hao, Y. (2018). An approach for noninvasive blood glucose monitoring based on bioimpedance difference considering blood volume pulsation. IEEE Access, 6, 51119–51129.

18.   Liu, L., Li, K., Qin, W., Wen, T., Li, L., Wu, J., & Gu, J. (2018). Automated breast tumor detection and segmentation with a novel computational framework of whole ultrasound images. Medical & Biological Engineering & Computing, 56(2), 183–199.

19.   Xiao, T., Liu, L., Li, K., Qin, W., Yu, S., & Li, Z. (2018). Comparison of Transferred Deep Neural Networks in Ultrasonic Breast Masses Discrimination. BioMed Research International, 2018, 1–9.

20.   Liu, Y., Qin, W., Li, R., Yu, S., He, Y., & Xie, Y. (2018). Investigation on the Neural Mechanism of Hypnosis-Based Respiratory Control Using Functional MRI. Contrast Media & Molecular Imaging, 2018.

21.   Zhao, W., Li, D., Niu, K., Qin, W., Peng, H., & Niu, T. (2018). Robust Beam Hardening Artifacts Reduction for Computed Tomography Using Spectrum Modeling. IEEE Transactions on Computational Imaging, 5(2), 333–342.

22.   Qin, W., Wu, J., Han, F., Yuan, Y., Zhao, W., Ibragimov, B., Xing, L. (2018). Superpixel-based and boundary-sensitive convolutional neural network for automated liver segmentation. Physics in Medicine and Biology, 63(9).

23.   Chen, Y., Wang, L., Li, F., Du, B., Choo, K. K. R., Hassan, H., & Qin, W. (2017). Air quality data clustering using EPLS method. Information Fusion.

24.   Li, J., Liu, Y., Nie, Z., Qin, W., Pang, Z., & Wang, L. (2017). An approach to biometric verification based on human body communication in wearable devices. Sensors (Switzerland).

25.   Wen, T., Li, L., Zhu, Q., Qin, W., Gu, J., Yang, F., & Xie, Y. (2017). GPU-accelerated Kernel Regression Reconstruction for Freehand 3D Ultrasound Imaging. Ultrasonic Imaging.

26.   Wen, T., Gu, J., Li, L., Qin, W., Wang, L., & Xie, Y. (2016). Nonlocal total-variation-based speckle filtering for ultrasound images. Ultrasonic Imaging, 38(4), 254–275.

27.   Guping JiangWenjian QinShoujun ZhouChangmiao Wang. (2015). A Survey on Medical Imaging Segmentation. Journal of Computer, 38(6), 1222–1242.

28.   Chen, X., Wen, T., Li, X., Qin, W., Lan, D., Pan, W., & Gu, J. (2014). Reconstruction of freehand 3D ultrasound based on kernel regression. BioMedical Engineering Online.

29.   Wen, T., Zhu, Q., Qin, W., Li, L., Yang, F., Xie, Y., & Gu, J. (2013). An accurate and effective FMM-based approach for freehand 3D ultrasound reconstruction. Biomedical Signal Processing and Control.

30.   Luo, Q., Qin, W., Wen, T., Gu, J., Gaio, N., Chen, S., … Xie, Y. (2013). Segmentation of abdomen MR images using kernel graph cuts with shape priors. BioMedical Engineering Online, 12(1).

31.   Yang, F., Qin, W., Xie, Y., Wen, T., & Gu, J. (2012). A shape-optimized framework for kidney segmentation in ultrasound images using NLTV denoising and DRLSE. BioMedical Engineering Online, 11.

32.         QIN, W., & GU, J. (2010). Multiple-modality Calibration of Video and Magnetic Tracker Data for 3D Appearance and Structure Modeling in Minimally Invasive Surgery. Journal of Image and Graphics, (7), 17.

Published Conference Papers:

1.        Qin W, Li Z, Gu J, Chen K, Zhang X. 1D infrared camera distortion based on polynomial model. In: Proceedings of the 2012 International Conference on Computer Application and System Modeling, ICCASM 2012. ; 2012.

2.        Yu S, Zhang Z, Liang X, et al. A Matlab Toolbox for Feature Importance Ranking. 2019 Int Conf Med Imaging Phys Eng. 2019.

3.        Liu X, Gu J, Xie Y, Xiong J, Qin W. A new approach to detecting ulcer and bleeding in wireless capsule endoscopy images. In: Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012. ; 2012. doi:10.1109/BHI.2012.6211688

4.        Qin W, Wen T, Zheng Z, et al. A pilot study on simulation of Ultrasound from MRI using ray-based model. In: Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012. ; 2012. doi:10.1109/BHI.2012.6211662

5.        Songhui D, Luo W, Hou J, et al. Computer Aided Cancer Regions Detection of Hepatocellular Carcinoma in Whole-slide Pathological Images based on Deep Learning. In: 2019 International Conference on Medical Imaging Physics and Engineering (ICMIPE2019). Shenzhen; 2019.

6.        Qiu T, Wen T, Qin W, Gu J, Wang L. Freehand 3D ultrasound reconstruction for image-guided surgery. In: Proceedings of 2011 International Symposium on Bioelectronics and Bioinformatics, ISBB 2011. ; 2011. doi:10.1109/ISBB.2011.6107667

7.        Wen T, Liu R, Liu L, Qin W, Li L, Gu J. GPU-based volume reconstruction for freehand 3D ultrasound imaging. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. ; 2017. doi:10.1109/EMBC.2017.8037661

8.        Luo Q, Qin WJ, Gu J. Kernel Graph Cuts Segmentation for MR Images with Intensity Inhomogeneity Correction. Vol 333-335.; 2013. doi:10.4028/

9.        Yuan Y, Meng MQ-H, Qin W, and Xing L. Liver Lesion Detection Based on Two-Stage Saliency Model with Modified Sparse Autoencoder. Med Image Comput Comput Assist Interv – MICCAI 2017 MICCAI 2017. 2017;3:577-585. doi:10.1007/978-3-319-66179-7

10.      Li L, Gu J, Wen T, Qin W, Xiao H, Yu J. Multiscale Geometric Active Contour Model and Boundary Extraction in Kidney MR Images. Vol 8423 LNCS.; 2014. doi:10.1007/978-3-319-06269-3_23

11.       Yuan Y, Qin W, Guo X, et al. Prostate segmentation with encoder-decoder densely connected convolutional network (ed-densenet). In: Proceedings - International Symposium on Biomedical Imaging. Vol 2019-April. ; 2019. doi:10.1109/ISBI.2019.8759498

12.      Yuan Y, Qin W, Ibragimov B, Han B, Xing L. RIIS-DenseNet: Rotation-Invariant and Image Similarity Constrained Densely Connected Convolutional Network for Polyp Detection. In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018. MICCAI 2018. Lecture Notes in Computer Science. ; 2014. doi:10.1007/978-3-319-67774-3_19

13.      Liu L, Qin W, Yang R, et al. Segmentation of breast ultrasound image using graph cuts and level set. In: IET Conference Publications. Vol 2015. ; 2015.

14.      Shen P, Qin W, Yang J, et al. Segmenting multiple overlapping nuclei in H&E stained breast cancer histopathology images based on an improved watershed. In: IET Conference Publications. ; 2015. doi:10.1049/cp.2015.0779

15.      Wan Z, Qin W, Song K, Wang B, Zhang D, Li L. Semi-Supervised Representation Learning for Infants Biliary Atresia Screening Using Deep CNN-Based Variational Autoencoder. In: International Conference on Mechatronics and Intelligent Robotics. Springer, Cham; 2018:1207-1212

Partial Issued Patents:

1.       Qin Wenjian, Luo Qing, Gu Jia. Method and System for Abdominal Soft Tissue MRI Image Segmentation. 2013104003112, Chinese Invention Patent.

2.       Qin Wenjian, Wen Tiexiang, Chen Ken, Xiao Hua, Li Zhicheng, Gu Jia. Method of Multimodal Medical Image Registration, 201310351477X, Chinese Invention Patent.

3.       Qin Wenjian, Gu Jia, Wen Tiexiang, Li Zhicheng. Method and System for Tumor Feature Extraction of Ultrasonic Imaging. 201410201896X, Chinese Invention Patent.

4.       Qin Wenjian, Wen Tiexiang, Li Ling, A Multimode Image-Based Surgical Navigation System, 2013102981426, Chinese Invention Patent.

5.       Qin Wenjian, Gu Jia, Wen Tiexiang, Zhang Dongwen, Li Zhicheng, Chen Ken, Method and System of Surgical Navigation, 2013101857582, Chinese Invention Patent.

6.       Qin Wenjian, Wen Tiexiang, Gu Jia, Xiao Hua, Li Ling. Method of Automatic Focus for Capsule Endoscopy, 2013103323429, Chinese Invention Patent.

7.       Gu Jia, Qin Wenjian, Zhang Dongwen, Wen Tiexiang. Multimodal Simulation Body Model, 2010106055103, Chinese Invention Patent.

8.       Gu Jia, Qin Wenjian. Method of Calibration for Medical Endoscopy, 2009101090860, Chinese Invention Patent.

9.       Chen Ken, Li Zhicheng, Qin Wenjian, Li Ling, Gu Jia, Remote surgery planning and navigation system, 201310036020X, Chinese Invention Patent.

Research Interests

Pattern Recognition and Medical Image Processing

Computational imaging



齐恒  硕士研究生  085211-计算机技术  

张旺  硕士研究生  085400-电子信息  

赖清佩  硕士研究生  085409-生物医学工程  

曾伟斌  硕士研究生  085400-电子信息  

欧阳效芸  硕士研究生  085210-控制工程  

叶欣婷  硕士研究生  085404-计算机技术  

赵汉卿  硕士研究生  085404-计算机技术  

侯嘉馨  硕士研究生  083100-生物医学工程  

乐美琰  硕士研究生  085210-控制工程  


唐璐妤  硕士研究生  083100-生物医学工程  

郑博匀  硕士研究生  085404-计算机技术  

刘琳  硕士研究生  085404-计算机技术  

刁颂辉  博士研究生  081104-模式识别与智能系统  

谭述东  硕士研究生  085404-计算机技术  

范博坤  硕士研究生  085404-计算机技术  

陈鑫  硕士研究生  085404-计算机技术  

刘祥  硕士研究生  085404-计算机技术  

张宇鑫  硕士研究生  085404-计算机技术  

彭月  博士研究生  081104-模式识别与智能系统  

郑邦炯  硕士研究生  085404-计算机技术  

陈富强  硕士研究生  085404-计算机技术  

涂人哲  硕士研究生  085404-计算机技术  

周佳慧  硕士研究生  085404-计算机技术  

芮浩晖  硕士研究生  085404-计算机技术  

杨世龙  硕士研究生  085404-计算机技术  

朱九赫  硕士研究生  085404-计算机技术  

韩钰佳  硕士研究生  085404-计算机技术  

熊兵  硕士研究生  085404-计算机技术  

段玉龙  硕士研究生  085409-生物医学工程  

黄凌风  硕士研究生  085404-计算机技术  

宋志臻  硕士研究生  085404-计算机技术  

侯嘉馨  博士研究生  081104-模式识别与智能系统