Weimin Zhou, PhD

Assistant Professor, Medical Imaging and Optical Sciences

Dr. Zhou is an Assistant Professor with appointments in the Department of Medical Imaging and the Wyant College of Optical Sciences at the University of Arizona (UA). Prior to joining UA in 2025, he was an Assistant Professor at the Global Institute of Future Technology at Shanghai Jiao Tong University (SJTU) from 2022 to 2024. He earned his Ph.D. in Electrical Engineering from Washington University in St. Louis (WashU) in 2020. During his Ph.D., he served as a Research Assistant in the Department of Biomedical Engineering at WashU and as a Visiting Scholar in the Department of Bioengineering at the University of Illinois Urbana-Champaign (UIUC). Following graduation, he joined the University of California, Santa Barbara (UCSB) as a Postdoctoral Scholar in the Department of Psychological & Brain Sciences, where he worked from 2020 to 2022.

Dr. Zhou directs the Computational Imaging and Visual Intelligence Laboratory (CIVIL) and conducts research at the intersection of image science and artificial intelligence/machine learning (AI/ML). His lab focuses on enhancing human and machine visual perception and developing advanced computational imaging methods to enable objective assessment and optimization of image quality, with the aim of improving diagnostic accuracy and interpretive efficiency in medical imaging. Research projects in CIVIL include deep generative models for medical image synthesis; AI/ML-established observer models for task-based image quality assessment; visual search and signal detection in medical images; and deep learning-based image reconstruction for optimizing task-based image quality. Dr. Zhou has been active in publishing research articles in peer-reviewed journals, such as IEEE Transactions on Medical Imaging, Medical Physics, Optics Express, Journal of Biomedical Optics, and Journal of Medical Imaging.

Dr. Zhou has been actively engaged in the scientific community. He is the recipient of the SPIE Community Champion Award and the SPIE Medical Imaging Cum Laude Award. He has also served as a Program Committee Member and a Session Chair for SPIE Medical Imaging, an Area Chair for the Conference on Health, Inference, and Learning (CHIL), an Area Chair for the Machine Learning for Health (ML4H) Symposium, and a reviewer for a wide range of academic journals. Find more information on his Optical Sciences webpage.

Degrees
  • PhD, Washington University, St. Louis, MO
Honors and Awards
  • SPIE Community Champion, The International Society for Optics and Photonics, 2020
  • Cum Laude Award, SPIE Medical Imaging, 2018

Select Publications

2023

Granstedt, J. L., W. Zhou, and M. A. Anastasio, "Approximating the Hotelling observer with autoencoder-learned efficient channels for binary signal detection tasks.", J Med Imaging (Bellingham), vol. 10, issue 5, pp. 055501, 2023 Sep. PMCID: PMC10520791  PMID: 37767114
Zhou, W., U. Villa, and M. A. Anastasio, "Ideal Observer Computation by Use of Markov-Chain Monte Carlo With Generative Adversarial Networks.", IEEE Trans Med Imaging, vol. 42, issue 12, pp. 3715-3724, 2023 Dec. PMCID: PMC10769588  PMID: 37578916

2022

Li, K., W. Zhou, H. Li, and M. A. Anastasio, "A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods.", IEEE Trans Med Imaging, vol. 41, issue 5, pp. 1114-1124, 2022 May. PMCID: PMC9128572  PMID: 34898433
Zhou, W., S. Bhadra, F. J. Brooks, H. Li, and M. A. Anastasio, "Learning stochastic object models from medical imaging measurements by use of advanced ambient generative adversarial networks.", J Med Imaging (Bellingham), vol. 9, issue 1, pp. 015503, 2022 Jan. PMCID: PMC8866417  PMID: 35229009

2021

Sidky, E. Y., J. Paul Phillips, W. Zhou, G. Ongie, J. P. Cruz-Bastida, I. S. Reiser, M. A. Anastasio, and X. Pan, "A signal detection model for quantifying overregularization in nonlinear image reconstruction.", Med Phys, vol. 48, issue 10, pp. 6312-6323, 2021 Oct. PMCID: PMC8697366  PMID: 34169538
Li, K., W. Zhou, H. Li, and M. A. Anastasio, "Assessing the Impact of Deep Neural Network-Based Image Denoising on Binary Signal Detection Tasks.", IEEE Trans Med Imaging, vol. 40, issue 9, pp. 2295-2305, 2021 Sep. PMCID: PMC8673589  PMID: 33929958

2020

Brown, J., S. Somo, F. Brooks, S. Komarov, W. Zhou, M. Anastasio, and E. Brey, "X-ray CT in Phase Contrast Enhancement Geometry of Alginate Microbeads in a Whole-Animal Model.", Ann Biomed Eng, vol. 48, issue 3, pp. 1016-1024, 2020 Mar. PMCID: PMC6874731  PMID: 31123843
Chen, Y., W. Zhou, C. K. Hagen, A. Olivo, and M. A. Anastasio, "Comparison of data-acquisition designs for single-shot edge-illumination X-ray phase-contrast tomography.", Opt Express, vol. 28, issue 1, pp. 1-19, 2020 Jan 06. PMCID: PMC7053502  PMID: 32118936
Zhou, W., H. Li, and M. A. Anastasio, "Approximating the Ideal Observer for Joint Signal Detection and Localization Tasks by use of Supervised Learning Methods.", IEEE Trans Med Imaging, vol. 39, issue 12, pp. 3992-4000, 2020 Dec. PMCID: PMC7768793  PMID: 32746143

2019

Zhou, W., H. Li, and M. A. Anastasio, "Approximating the Ideal Observer and Hotelling Observer for Binary Signal Detection Tasks by Use of Supervised Learning Methods.", IEEE Trans Med Imaging, vol. 38, issue 10, pp. 2456-2468, 2019 Oct. PMCID: PMC6858982  PMID: 30990425

2017

Lou, Y., W. Zhou, T. P. Matthews, C. M. Appleton, and M. A. Anastasio, "Generation of anatomically realistic numerical phantoms for photoacoustic and ultrasonic breast imaging.", J Biomed Opt, vol. 22, issue 4, pp. 41015, 2017 Apr 01. PMCID: PMC5282404  PMID: 28138689