Biography

Dr. Dahong Qian is a professor in Biomedical Engineering at Shanghai Jiao Tong University. He had held various engineering and management positions at Analog Devices and OmniVision, etc. From 2013 to 2017, he was a professor at Zhejiang University Medical School. His research areas include AI in medicine and medical data processing, medical microelectronics and micro sensors.

Education background

1997-2002 Ph.D. in Computer Science, Harvard University
1989-1992 M.S.E., the University of Texas at Austin
1984-1988 B.S.E., Zhejiang University

Work Experience

2017 – present

Professor, School of Biomedical Engineering, Shanghai Jiao Tong University

2013 – 2017

Professor, School of Medicine, Zhejiang University

Areas of Research Interests

Clinical-driven AI-based computer aided diagnostics and therapy;

Intelligent endoscopic systems and algorithms for minimal invasive surgery;

Micro devices and embedded AI algorithms for medical robotics;

Wearable and implantable devices and machine learning-based data analysis;

Teaching

Fall Semester 2019，2020: Undergraduate Course: BI 136: BioDesign

Spring Semester 2019, 2020: Graduate Course: Artificial Intelligence in Medicine

Selected Publications

1. Dingyi Liu, Xin Peng, Xiaoqing Liu, Yiming Li, , Yiming Bao, Jianwei Xu, Xianzhang Bian, Wei Xue, Dahong Qian, “A Real-Time System Using Deep Learning to Detect and Track Ureteral Orifices During Urinary Endoscopy”, Computers in Biology and Medicine, vol 128, January 2021.

2. Jun Wang, Yiming Bao, Yaofeng Wen, Hongbing Lu, Hu Luo, Yunfei Xiang, Xiaoming Li, Chen Liu, DahongQian, “Prior-Attention Residual Learning for More Discriminative COVID-19 Screening in CT Images”, IEEE Transactions on Medical Imaging, pp. 0, November 2020.

3. Xiaojun Guan, Shaoze Wang, Pingding Kuang, Haitong Lu, Minming Zhang, Dahong Qian, Xiaojun Xu, “The usefulness of imaging quantification in discriminating non-calcified pulmonary hamartoma from adenocarcinoma”, Frontiers in Oncology, vol. 10, October 22, 2020.

4. Min Zhang, Yiming Bao, Weiwei Rui, Chengfang Shangguan, Jiajun Liu, Jianwei Xu, Xiaozhu Lin, Miao Zhang, Xinyun Huang, Yilei Zhou, Qian Qu, Hongping Meng, Dahong Qian, Biao Li, “Performance of 18F-FDG PET/CT Radiomics for Predicting EGFR Mutation Status in Patients with Non-Small Cell Lung Cancer”, Frontiers in Oncology, vol 10, October 8, 2020.

5. Cheng Yuan, Yujin Tang, Dahong Qian, “Ovarian Cancer Prediction in Proteomic Data Using Stacked Asymmetric Convolution”, MICCAI 2020, Lima, Peru, October 4-8, 2020.

6. Ruifei Zhang, Guanbin Li, Zhen Li, Shuguang Cui, Dahong Qian, Yizhou Yu, “Adaptive Context Selection for Polyp Segmentation”, MICCAI 2020, Lima, Peru, October 4-8, 2020.

7. Jingyi Wang, Xu Zhao, Qingtian Ning, Dahong Qian, “AEC-Net: Attention and Edge Constraint Network for Medical Image Segmentation”, 2020 42nd Annual International Conference of the IEEE EMBC, Canada, vol. 210, July 20-24, 2020.

8. Li Tong, Chen Ning, Wen Yaofeng, Xu Xiang, Ye Cong, Zhang Shaodan, Qian Dahong, Liang Yuanbo, “Differentiation of primary open angle-closure glaucoma and primary open angle glaucoma based on disc image with a deep learning method”, ARVO(Association for Research in Vision and Ophthalmology) 2020, Baltimore, MD, US, May 3-7, 2020.

9. Jun Wang, Xiaorong Chen, Hongbing Lu, Lichi Zhang, Jianfeng Pan, Yong Bao, Jiner Su, Dahong Qian, “Feature-shared adaptive-boost deep learning for invasiveness classification of pulmonary sub-solid nodules in CT images”, Medical Physics, vol. 47, No. 4, pp1738-1749, February 5, 2020.

10. ZiJie Zhang, KaiBin Lin, ZhaoRui Zuo, DaHong Qian, Dong Huang, JingBo Li, “Prediction for atrial fibrillation recurrence after catheter ablation using an artificial intelligence-assisted coronary sinus electrogram”, AHA2019, US, November 16-18, 2019.

11. Yi Su, Qingchang Tian, Dingyi Pan, Lanlan Hui, Yanni Chen, Qi Zhang, Wei Tian, Jie Yu, Shen Hu, Yang Gao, Dahong Qian, Tian Xie, Ben Wang, “Antibody-Functional Microsphere-Integrated Filter Chip with Inertial Microflow for Size–Immune-Capturing and Digital Detection of Circulating Tumor Cells”, ACS Applied Materials & Interfaces, vol. 43, July 30, 2019.

12. Xin Peng, Dingyi Liu, Yiming Li, Wei Xue, Dahong Qian, “Real-Time Detection of Ureteral Orifice in Urinary Endoscopy Videos Based on Deep Learning”, EMBC2019, Berlin, Germany, July 23-27, 2019.

13. Zenghui Cheng, Jiping Zhang, Naying He, Yan Li, Yaofeng Wen, Hongmin Xu, Rongbiao Tang, Zhijia Jin, E. Mark Haacke, Fuhua Yan, Dahong Qian, “Radiomic Features of the Nigrosome-1 Region of the Substantia Nigra: Using Quantitative Susceptibility Mapping to Assist the Diagnosis of Idiopathic Parkinson’s Disease”, Frontiers in Aging Neuroscience, vol. 11, pp. 167, July 16, 2019.

14. Lixia Lou, Longzhao Yang, Xin Ye, Yan Zhu, Shaoze Wang, Lingling Sun, Dahong Qian, Juan Ye, “A Novel Approach for Automated Eyelid Measurements in Blepharoptosis Using Digital Image Analysis”, Current Eye Research, vol.44, No. 10, pp. 1075-1079, May 31, 2019.

15. Shaoze Wang, Hao Zhang, Dahong Qian, “A Semi-supervised Bleeding Detection Method in Wireless Capsule Endoscopy”, Digestive Disease Week® (DDW) 2019, San Diego, CA, USA, May 18-21, 2019.

16. Jun Wang, Jiawei Wang, Yaofeng Wen, Hongbing Lu, Tianye Niu, Jiangfeng Pan, Dahong Qian, “Pulmonary Nodule Detection in Volumetric Chest CT Scans Using CNNs-based Nodule-Size-Adaptive Detection and Classification”, IEEE Access, vol.7, No.1, pp. 46033~46044, March 29, 2019.

17. Lin Zhou, Kun Wang, Hao Sun, Simin Zhao, Xianfeng Chen, Dahong Qian, Hongju Mao, Jianlong Zhao, “Novel Graphene Biosensor Based on the Functionalization of Multifunctional Nano-bovine Serum Albumin for the Highly Sensitive Detection of Cancer Biomarkers”, Nano-Micro Letters, vol.250, pp. 13, February 20, 2019.

18. Zhaorui Zuo, Kun Wang, Libing Gao, Vincent Ho, Hongju Mao, Dahong Qian, “A novel mass-producible capacitive sensor with fully symmetric 3D structure and microfluidics for cell detection”, Sensors 2019, vol.19, pp. 325, January 15, 2019.