BIOGRAPHICAL SKETCH

EDUCATION/TRAINING

INSTITUTION AND LOCATION	DEGREE (if applicable)	Completion Date MM/YYYY	FIELD OF STUDY
Southeast University, Nanjing, China	B.Sc.	06/2000	Biomedical Engineering
Southeast University, Nanjing, China	M.Sc.	06/2003	Biomedical Engineering
The Chinese University of Hong Kong, Hong Kong, China	Ph.D.	09/2009	Computer Science and Engineering
University of North Carolina, Chapel Hill, USA	Postdoctoral	04/2010	Radiology

 

A.   Personal Statement

My long-standing research interests fall in Medical UltraSound Image Computing ( MUSIC ) and image guided surgery. I established the MUSIC lab in 2017. The MUSIC lab conducts cutting-edge research on artificial intelligence (AI) in medical ultrasound. Currently the MUSIC lab has >30 members, including five staff members, six postdocs and 30 graduate students. Our lab are world leaders in the following research areas: ultrasound image analysis; multi-modality image registration; breast cancer detection in ABUS. Research in my lab has been continuously supported by two regular grants from the National Natural Science Foundation in China (NSFC) and four Shenzhen Basic Research grants since 2010. I serve as the local chair of the 22^ndInternational Conference On Medical Image Computing & Computer Assisted Intervention (MICCAI 2019). I have published >60 papers in peer-reviewed professional journals and have presented at leading conferences. I am currently mentoring three postdoctoral fellows, one PhD candidate and 10 MSc candidates.

 

B.   Positions and Honors

Positions and Employment

06/2003–5/2006          Engineer, Mindray Biomedical Electronic Co.Ltd, Shenzhen, China

04/2010 – present       Assistant Professor (2010), Associate Professor (2012), Professor (2017), School of Biomedical Engineering, Health center, Shenzhen University

05/2016 – present       Associate Dean, School of Biomedical Engineering, Health center, Shenzhen University

 

Organizing International Meetings

1.    Co-organizer, the 1st Medical Image Computing Seminar, December 11-12th, 2014, Shenzhen.

2.    Local Chair, the 22nd International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI 2019), Oct. 13-17th, 2019, Shenzhen, China

 

Other Experience and Honors

 

 

C.   Contributions to Science (*: corresponding/co-corresponding author)

A full list of my publications (in a total of 74) is enclosed at the end of this document.

 

1.    Intelligent prenatal ultrasound

User dependence is one of the main challenges of ultrasound diagnosis. Specifically, both acquisition of the standard plane and measurement of biometric parameters are crucial for medical ultrasound diagnosis. However, these processes require substantial experience and a thorough knowledge of human anatomy. To the best of our knowledge, for the first time, we propose to automate standard plane detection and biometry measurement sequentially in ultrasound. Our developed learning algorithms include random forest, convolutional neural network, recurrent neural network and spatio-temporal regression. All these projects were carried out jointly with local hospitals and companies in Shenzhen, Guangzhou and Hong Kong. Some of them are being commercialized.

 

2.    Multimodal Medical Image Registration

Registration and fusion of magnetic resonance (MR) and 3D transrectal ultrasound (TRUS) images of the prostate gland can provide high-quality guidance for prostate interventions. However, accurate MR-TRUS registration remains a challenging task, due to the great intensity variation between the two modalities, the lack of intrinsic fiducials within the prostate, the large gland deformation caused by the TRUS probe insertion, and distinctive biomechanical properties in patients and prostate zones. To address these challenges, a personalized model-to-surface registration approach is proposed in this study. Our main contributions can be threefold. First, a new personalized statistical deformable model (PSDM) is proposed with the finite element analysis and the patient-specific tissue parameters measured from the ultrasound elastography. Second, a hybrid point matching method is developed by introducing the modality independent neighborhood descriptor (MIND) to weight the Euclidean distance between points to establish reliable surface point correspondence. Third, the hybrid point matching is further guided by the PSDM for more physically plausible deformation estimation. Our approach provides more accurate and robust MR-TRUS registration than state-of-the-art methods do.

 

D.   Research Support

Ongoing Research Support

NSFC project (61571304)                                           01/01/2016 to 12/31/2019

Dong Ni, PI                                                                  ￥797,000 (direct cost)

Partial Non-rigid Registration of Prostate Multi-modal Image Based on Personalized Deformable Model and Hybrid Fuzzy Correspondence

 

Completed Research Support

NSFC project (61101026)                                           01/01/2012 to 12/31/2014

Dong Ni, PI                                                                  $220,000

Facial Standard plane localization from 3d medical ultrasound

 

NSFC project (81270707)                                           01/01/2013 to 12/31/2016

Dong Ni, Co-PI                                                            $280,000

Intelligent medical ultrasound ： Automatic standard plane localization and biometric measurement

 

Shenzhen-Hong Kong Joint project (JSE201109150013A)      01/01/2013 to 12/31/2015

Dong Ni, PI                                                                  $1,600,000

Development of US-MRI fusion guided prostate biopsy system: plan, training and intelligent guidance during surgery

 

E.    Peer-reviewed publications (*: corresponding author)

1.      Li, J., Wang, Y.*, Lei, B., Cheng, J. Z., Qin, J., Wang, T., Li, S.*, Ni, D.* (2017). Automatic Fetal Head Circumference Measurement in Ultrasound using Random Forest and Fast Ellipse Fitting. IEEE Journal of Biomedical and Health Informatics.

2.      Hao Chen, Lingyun Wu, Qi Dou, Jing Qin, Shengli Li, Jie-Zhi Cheng*, Dong Ni*, and Pheng-Ann Heng, " Ultrasound Standard Plane Detection Using a Composite Neural Network Framework," in IEEE Transactions on Cybernetics , Vol. 47, No. 6, pp. 1576 – 1586, March 2017.

3.      L. Wu; J. Z. Cheng; S. Li; B. Lei; T. Wang; D. Ni*, "FUIQA: Fetal Ultrasound Image Quality Assessment With Deep Convolutional Networks," in IEEE Transactions on Cybernetics , Vol. 47, No. 5, pp. 1336 – 1349, March 2017.

4.      B. Lei, P. Yang, T. Wang, S. Chen and D. Ni*, "Relational-Regularized Discriminative Sparse Learning for Alzheimer’s Disease Diagnosis," in IEEE Transactions on Cybernetics, vol. 47, no. 4, pp. 1102-1113, April 2017.　

5.      Lei B, Jiang F, Chen S, Ni D*, Wang T. Longitudinal Analysis for Disease Progression via Simultaneous Multi-Relational Temporal-Fused Learning. Frontiers in aging neuroscience. 2017;9 (SCI, 中科院二区)

6.      Sihong Chen, Jing Qin, Xing Ji, Baiying Lei, Tianfu Wang, Dong Ni* and Jie-Zhi Cheng*, “Automatic Scoring of Multiple Semantic Attributes with Multi-task Feature Leverage: A Study on Pulmonary Nodules in CT Images”, IEEE Transactions on Medical Imaging, Vol. 36, No. 3, pp. 802-814 , March 2017.

7.      Dong Ni, Xing Ji, Min Wu, Wenlei Wang, Xiaoshuang Deng, Zhongyi Hu, Tianfu Wang, Dinggang Shen, Jie-Zhi Cheng,*, Huifang Wang,*, Automatic Cystocele Severity Grading in Transperineal Ultrasound by Random Forest Regression. Pattern Recognition, 63: 551-560, 2017.03.

8.      Lei, B., Chen, S., Ni, D.*, & Wang, T*. (2016). Discriminative Learning for Alzheimer's Disease Diagnosis via Canonical Correlation Analysis and Multimodal Fusion. Frontiers in Aging Neuroscience,  online.

9.      B. Lei, W. Li, Y. Yao, S. Chen, D. Ni* and T. Wang*, “Multi-modal and Multi-layout Discriminative Learning for Placental Maturity Staging”, Pattern Recognition, 63: 719-730, 2017.03

10.   B. Lei, Y. Yao, W. Li, S. Li, S. Chen, D. Ni* and T. Wang*，“Discriminative Learning for Automatic Staging of Placental Maturity via Multi-layer Fisher Vector”, Scientific Reports, 5, doi: SREP12818, 2015

11.   B. Lei, E.-L. Tan, S. Chen, W. Li, D. Ni, Y. Yao*, and T. Wang*. "Automatic placental maturity grading via hybrid learning." Neurocomputing, vol.223, pp.86-102, 2017.

12.   Y. Song, E. Tan, X. Jiang, J. Cheng, D. Ni, S. Chen, B. Lei*,and T. Wang*. "Accurate Cervical Cell Segmentation from Overlapping Clumps in Pap Smear Images." IEEE Transactions on Medical Imaging, vol.36 (1), pp.288-300. 2017.

13.   Jie-Zhi Cheng, Dong Ni, Yi-Hong Chou*, Jing Qin, Chui-Mei Tiu, Yeun-Chung Chang, Chiun-Sheng Huang, Dinggang Shen*, Chung-Ming Chen*. “Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans,” Scientific Reports, 6: 24454, 2016.

14.   Yi Wang, Dong Ni, Jing Qin*, Ming Xu, Xiaoyan Xie, and Pheng-Ann Heng, Patient-specific Deformation Modelling via Elastography: Application to Image-guided Prostate Interventions. Scientific Report, 2016, 6: 27386.

15.   Shaoyi Du, Yanrong Guo, Gerard Sanroma, Dong Ni*, Guorong Wu, Dinggang Shen*, Building dynamic population graph for accurate correspondence detection. Medical image analysis, 2015，26(1), 256-267.

16.   Jin, Yan, Chong-Yaw Wee, Feng Shi, Kim-Han Thung, Dong Ni*, Pew-Thian Yap, and Dinggang Shen*. "Identification of infants at high‐risk for autism spectrum disorder using multiparameter multiscale white matter connectivity networks." Human Brain Mapping 36, no. 12 (2015): 4880-4896.

17.   Li, Gang, Tianming Liu, Dong Ni*, Weili Lin, John H. Gilmore, and Dinggang Shen*. "Spatiotemporal patterns of cortical fiber density in developing infants, and their relationship with cortical thickness." Human brain mapping 36, no. 12 (2015): 5183-5195.

18.   Wang, Yi, Jie-Zhi Cheng*, Dong Ni*, Muqing Lin, Jing Qin, Xiongbiao Luo, Ming Xu, Xiaoyan Xie, and Pheng Heng. "Towards Personalized Statistical Deformable Model and Hybrid Point Matching for Robust MR-TRUS Registration", IEEE Transactions on Medical Imaging, 2016，35(2): 589-604.

19.   Chen Hao, Ni Dong*, Qin Jing*, Li Shengli, Yang Xin, Wang Tianfu, Heng Pheng-Ann. Standard Plane Localization in Fetal Ultrasound via Domain Transferred Deep Neural Networks, Biomedical and Health Informatics, IEEE Journal of , 2015, 19(5): 1627-1636.

20.   Youyi Song, Ling Zhang, Siping Chen, Dong Ni, Baiying Lei, Tianfu Wang, "Accurate Segmentation of Cervical Cytoplasm and Nuclei Based on Multiscale Convolutional Network and Graph Partitioning," in Biomedical Engineering, IEEE Transactions on, vol.62, no.10, pp.2421-2433, Oct. 2015

21.   Lei, Baiying, Ee-Leng Tan, Siping Chen, Dong Ni*, and Tianfu Wang*. "Saliency-driven image classification method based on histogram mining and image score." Pattern Recognition 48, no. 8 (2015): 2567-2580.

22.   Lei, Baiying, Ee-Leng Tan, Siping Chen, Liu Zhuo, Shengli Li, Dong Ni*, and Tianfu Wang*. "Automatic Recognition of Fetal Facial Standard Plane in Ultrasound Image via Fisher Vector." Plos One, (2015): e0121838.

23.   Li, Qiaoliang, Suwen Qi, Yuanyuan Shen, Dong Ni*, Huisheng Zhang, and Tianfu Wang. "Multispectral Image Alignment With Nonlinear Scale-Invariant Keypoint and Enhanced Local Feature Matrix.", IEEE Geoscience and Remote Sensing Letters, 2015, 12(7): 1551-1555.

24.   Dong Ni, Xin Yang, Xin Chen, Chien-Ting Chin, Siping Chen, Pheng Ann Heng, Shengli Li, Jing Qin, Tianfu Wang, Standard Plane Localization in Ultrasound by Radial Component Model and Selective Search, Ultrasound in Medicine & Biology, 2014, 40(11): 2728-2742. (SCI)

25.   Lei Baiying, Tan Ee-Leng, Chen Siping, Ni Dong*, Wang Tianfu*, and Lei Haijun, Reversible watermarking scheme for medical image based on differential evolution. Expert Systems with Applications, 41(7): 3178-3188, 2014. (SCI)

26.   Song, Y., Ni, D., Zeng, Z., He, L., Chen, S., Lei, B.*, & Wang, T.* (2014). Automatic Vaginal Bacteria Segmentation and Classification Based on Superpixel and Deep Learning. Journal of Medical Imaging and Health Informatics, 4(5), 781-786.

27.   B. Lei, F. Zhou, E-L Tan, D. Ni, S. Chen*, and T. Wang*, “Optimal and Secure Audio Watermarking Scheme Based on Self-MCIaptive Particle Swarm Optimization and Quaternion Wavelet Transform”, Signal Processing, vol. (113), pp. 80-94, 2015

28.   B. Lei, S. Chen, D. Ni, H. Lei, T. Wang* and F, Zhou*, “Optimal image watermarking scheme based on chaotic map and quaternion wavelet transform", Nonlinear Dynamics, vol.78(4), pp.2897-2907, 2014

29.   Li, Qiaoliang, Dong Ni, Wanguan Yi, Siping Chen, Tianfu Wang, and Xin Chen. "Use of Optical Flow to Estimate Continuous Changes in Muscle Thickness from Ultrasound Image Sequences." Ultrasound in Medicine & Biology, 2013, 39(11): 2194-2201.

30.   Wang, W.M., Qin, J., Zhu L., Ni, D.*, et al., Detection and Measurement of Fetal Abdominal Contour in Ultrasound Images via Local Phase Information and Iterative Randomized Hough Transform, Bio-Medical Materials and Engineering, 2014, 24(1): p.1261-1267.

31.   Baiying Lei, Tianfu Wang, Siping Chen, Dong Ni*, and Haijun Lei, Comments on “an SVD audio watermarking approach using chaotic encrypted images”，ICIC Express Letters, 2013, 7(9): p. 1-EL13-0210.

32.   Li, Xinyao，Yao, Yuan，Ni, Dong，Chen, Siping，Li, Shengli，Lei, Baiying*，Wang, Tianfu*，Automatic staging of placental maturity based on dense descriptor，Bio-medical Materials and Engineering，2014，24（6）：2821-2829.

33.   Wang Liansheng, Qin Jing, Chen Yanping, Ni Dong*, Sparse imaging of epicardial potentials for patients with WPW syndrome, International Journal of Cardiology, 163(2), S4, 2013.

34.   Ni, D., Chan, W.Y., Qin, J., Chui, Y.P., Qu, Y.G., Ho, S.S.M., and Heng, P.A., A virtual reality simulator for ultrasound guided organ biopsy training, IEEE on Computer Graphics and Application, 2011, 31(2): p. 36-48.

35.   Ni, D., Ultrasound image enhancement and speckle mitigation method. The Journal of the Acoustical Society of America, 2010.128(5): p.3277.

36.   Ni, D., Chui, Y.P., Qu, Y.G., Yang, X., Qin, J., Wong, T.T., Ho, S.S.H., and Heng, P.A., Reconstruction of volumetric ultrasound panorama based on improved 3D SIFT. Computerized Medical Imaging and Graphics, 2009, 33(7): p. 559-566.

37.   Chan, W.Y., Ni, D., Pang, W.M., Qin, J., Chui, Y.P., Yu, S.C.H., and Heng, P.A., Learning ultrasound-guided needle insertion skills through an edutainment game, LNCS Transactions on Edutainment IV, 2009, 6250: p. 200-214.

38.   Yang, X., Yu, L., Li, S., Wang, X., Wang, Ni, D.* Qin, J., Pheng-Ann Heng. (2017). Towards Automatic Semantic Segmentation in Volumetric Ultrasound. Medical Image Computing and Computer Assisted Intervention − MICCAI 2017.

39.   Lingyun Wu, Xin Yang, Shengli Li, Tianfu Wang, Pheng-Ann Heng, Dong Ni*，Cascaded Fully Convolutional Networks for Automatic Prenatal Ultrasound Image Segmentation，in: Proceedings of 2017 IEEE International Symposium on Biomedical Imaging(ISBI 2017), Melbourne, Australia, 2017, Apr 18-21©IEEE.

40.   B. Lei*,P. Yang, D. Ni, and T. Wang, "Longitudinal Analysis for Mild Cognitive Impairment Identification Via Fused Group Learning with Smooth Regularization”, in: Proceedings of 2017 IEEE International Symposium on Biomedical Imaging(ISBI 2017),Melbourne,Australia,2017,Apr 18-21©IEEE.

41.   Z. Yu, D. Ni, S. Chen, J. Qin, S. Li, T. Wang, and B. Lei*,"Hybrid Dermoscopy Image Classification Framework Based on Deep Convolutional Neural Network and Fisher Vector", in: Proceedings of 2017 IEEE International Symposium on Biomedical Imaging (ISBI 2017),Melbourne,Australia,2017,Apr 18-21©IEEE.

42.   Z. Yu, S. Li, S. Chen, D. Ni, B. Lei*,and T. Wang*,"Fetal Facial Standard Plane Recognition via Very Deep Convolutional Networks", in: Proceedings of 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’16),pp.627-630,Orlando,Florida,USA,2016,Aug 16-20.(oral)

43.   Y. Song, J-Z Cheng, D. Ni, S. Chen, B. Lei*,and T. Wang*,"Segmenting Overlapping Cervical Cell in Pap Smear Images", in: Proceedings of 2016 IEEE International Symposium on Biomedical Imaging (ISBI 2016),pp.1159-1162,Prague,Czech,2016,Apr 13-16©IEEE.

44.   Chen, S., Ni, D., Qin, J., Lei, B., Wang, T., & Cheng, J. Z. (2016, October). Bridging Computational Features Toward Multiple Semantic Features with Multi-task Regression: A Study of CT Pulmonary Nodules. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 53-60). Springer International Publishing.

45.   Ni D, Ji X, Gao Y, et al. Automatic Cystocele Severity Grading in Ultrasound by Spatio-Temporal Regression[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer International Publishing, 2016: 247-255.

46.   Y. Song, J-Z Cheng, D. Ni, S. Chen, B. Lei, T. Wang, "Segmenting Individual Cervical Cell in Pap Smear Images ", in: Proceedings of 2016 IEEE International Symposium on Biomedical Imaging (ISBI 2016), Prague, Czech, Apr 13-16©IEEE

47.   Y. Zhuo, D. Ni, S. Chen, B. Lei, T. Wang, "Adaptive Ensemble Manifold Learning for Neuroimaging Retrieval", in: Proceedings of 2016 IEEE International Symposium on Biomedical Imaging (ISBI 2016), Prague, Czech, Apr 13-16©IEEE

48.   W. Li, Y. Yao, D. Ni, S. Chen, B. Lei, T. Wang, "Placental Maturity Evaluation Via Feature Fusion And Discriminative Learning.", in: Proceedings of 2016 IEEE International Symposium on Biomedical Imaging (ISBI 2016), Prague, Czech, Apr 13-16©IEEE

49.   Baiying Lei, Siping Chen, Dong Ni* and Tainfu Wang*, “Joint Learning of Multiple Longitudinal Prediction Models by Exploring Internal Relations”, MLMI 2015

50.   Wang Y, Ni D*, Qin J, et al. Towards personalized biomechanical model and MIND-weighted point matching for robust deformable MR-TRUS registration[C]//International Workshop on Computer-Assisted and Robotic Endoscopy. Springer, Cham, 2014: 121-130.(Oral)

51.   Wang Yi, Ni Dong*, Qin Jing, Yang Xin, Xie Xiaoyan, Lin Muqing, Pheng Ann Heng, Personalized modeling of prostate deformation based on elastography for MRI-TRUS registration, ISBI 2014: 782-785.

52.   Chen Hao, Ni Dong*, Yang Xin, Li Shengli, Heng Pheng Ann. Fetal Abdominal Standard Plane Localization through Representation Learning with Knowledge Transfer. In Machine Learning in Medical Imaging, Springer International Publishing, MICCAI 2014: 125-132.

53.   Lei, B., Zhuo, L., Chen, S., Li, S., Ni, D.*, & Wang, T.* (2014, April). Automatic recognition of fetal standard plane in ultrasound image. In Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on (pp. 85-88). IEEE.

54.   Yang Xin, Ni Dong *, Qin Jing, Li Shengli, Wang Tianfu, Chen Siping. Standard plane localization in ultrasound by radial component, ISBI 2014: 1180-1183.

55.   Ni, D., Li, T.M., Yang, X., Qin, J., et al. Selective Search and Sequential Detection for Standard Plane Localization in Ultrasound. Abdominal Imaging. Computation and Clinical Applications. Springer Berlin Heidelberg, 2013. 203-211. (Oral)

56.   Baiying Lei, Dong Ni*, Tianfu Wang, Siping Chen, Haijun Lei, Object recognition based on adaptive bag of feature and discriminative learning, ICIP 2013.

57.   Ni Dong, Yang Yong, Li Shengli, Qin Jing, Ouyang Shuyuan, Wang Tianfu, Heng Pheng Ann, Learning based automatic head detection and measurement from fetal ultrasound images via prior knowledge and imaging parameters, The 2013 International Symposium on Biomedical Imaging (ISBI), 2013.04.07-11, San Francisco, USA, 2013. 

58.   Ni, D., Qu, Y.G., Yang, X., Chui, Y.P., Wong, T.T., Ho, S.S.M., and Heng, P.A., Volumetric ultrasound panorama based on 3D SIFT. 11th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2008, 5242: p. 52-60. (SCI)

59.   Ni, D., Chan, W.Y., Qin, J., Qu, Y.G., Chui, Y.P., Ho, S.S.M., and Heng, P.A., An ultrasound-guided organ biopsy simulation with 6DOF haptic feedback. 11th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2008, 5242: p. 551-559. (SCI)

60.   Dong Ni, Xin Chen, Wanguan Yi, Yong-Ping Zheng, Zhenyu Zhu, Shing-Chow Chan, In Vivo Behavior of Human Muscle During Isometric Ramp Contraction: A Simultaneous EMG, MMG and Ultrasonography Investigation, Proceedings of 2012 International Conference on Signal Processing, Communications and Computing, 2012, Hong Kong.

61.   Ni, D., Chen, S.P., Xiang N.F., Wang T.F.，Segmentation of the Left Ventricle Myocardium in Echocardiography Based on T-Snake Model，The 6th International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2012)

62.   Ni, D., Chen, S.P., Chen W.S., Wang T.F., 3D Segmentation of Echocardiographic Images Based On Deformable Models，The 6th International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2012)

63.   Ni, D., Li Q.L., Chen S.P., and Wang T.F., Three-Dimensional Registration of Ultrasound and CT Based on Vessels, The 6th International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2012)

64.   Ni, D., Chen, S.P., Sun, H.M., and Wang, T.F., Modeling of 3D left ventricular motion to evaluate paced myocardial function, 2010 3rd International Conference on  Biomedical Engineering and Informatics (BMEI): p. 384-388. (EI)

65.   Qin, J., Pang, W.M., Binh P. Nguyen, Ni, D., and Chui, C.K., Particle-based simulation of blood flow and vessel wall interactions in virtual surgery, Proceedings of the 2010 Symposium on Information and Communication Technology: p. 128-133.

66.   Chan, W.Y., Ni, D., Pang, W.M., Qin, J., Chui, Y.P., and Heng, P.A., Make it fun: an edutainment game for ultrasound-guided needle insertion training. International Simulation And Gaming Association 40th Annual Conference, 2009.