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Jinghao Zhou, PhD

Academic Title:

Associate Professor

Primary Appointment:

Radiation Oncology

Education and Training

Tsinghua University, BE, Biomedical Engineering, 1998
Rutgers, the State University of New Jersey, MS, Statistics, 2006         
Rutgers, the State University of New Jersey, PhD, Biomedical Engineering, 2008


Dr. Zhou have a broad background of developing and evaluating the medical image analysis methods in clinic usage, with the specific training and expertise in radiotherapy as well as research on medical image analysis and modeling. 

Dr. Zhou's research interests include developing robust image analysis methods and building radiotherapy software systems for clinic practices. As co-investigator on several state- and industry-funded grants, Dr. Zhou laid the groundwork for the proposed research by developing novel computer aided cancer detection and segmentation, registration, radiotherapy system. In addition, he successfully administered the projects, collaborated with physicians and researchers, and produced many peer-reviewed publications. 

Research/Clinical Keywords

Medical Physics, Image Analysis, Computational Modeling, Artificial Intelligence, Machine Learning, Deep Learning

Highlighted Publications

Zhou, J., Yan, Z., Lasio, G., Huang, J., Zhang, B., Sharma, N., Prado, K. and D’Souza, W., 2015. Automated compromised right lung segmentation method using a robust atlas-based active volume model with sparse shape composition prior in CT. Computerized Medical Imaging and Graphics46, pp.47-55.

Amin, N.P., Romar, L., Shipman, K., Zhou, J., Lasio, G. and Levy, K., 2019. Incidental coronary artery calcium on radiation simulation scans identifies patients for preventive therapy. International Journal of Radiation Oncology, Biology, Physics105(1), pp.E38-E39.

Yang, D., Lasio, G., Zhang, B., Yi, B., Chen, S., Zhang, Y., Macvittie, T.J., Metaxas, D., Zhou, J., Automated Pulmonary Fibrosis Segmentation Using a 3D Multi-Scale Convolutional Encoder-Decoder Approach in Thoracic CT for the Rhesus Macaque with Radiation-Induced Lung Damage. Journal of Signal Processing Systems. 2020 Oct 27:1-11.

Wang G, Zhai S, Lasio G, Zhang B, Yi B, Chen S, Macvittie TJ, Metaxas D, Zhou J, Zhang S. Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis from Lung CT Scans with Multi-Scale Guided Dense Attention. IEEE transactions on medical imaging. 2021.