2026
A nonlinear channelized model observer using Box‑Cox transformation
Weimin Zhou
SPIE Medical Imaging 2026: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Medical image denoising with task‑based image‑adaptive denoising CNN
Wentao Chen, Weimin Zhou
SPIE Medical Imaging 2026: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Approximating the ideal observer for joint signal detection and estimation tasks by the use of Markov-Chain Monte Carlo with generative adversarial networks
Dan Li, Kaiyan Li, Weimin Zhou, Mark A Anastasio
Journal of Medical Imaging
[Paper]
Ambient denoising diffusion generative adversarial networks for establishing stochastic object models from noisy image data
Xichen Xu, Wentao Chen, Weimin Zhou
SPIE Medical Imaging 2025: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Task-based regularization in penalized least-squares for binary signal detection tasks in medical image denoising
Wentao Chen, Tianming Xu, Weimin Zhou
SPIE Medical Imaging 2025: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Using gradient of Lagrangian function to compute efficient channels for the ideal observer
Weimin Zhou
SPIE Medical Imaging 2025: Image Perception, Observer Performance, and Technology Assessment
[Paper]
2024
AmbientCycleGAN for establishing interpretable stochastic object models based on mathematical phantoms and medical imaging measurements
Xichen Xu, Wentao Chen, Weimin Zhou
SPIE Medical Imaging 2024: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Ambient-Pix2PixGAN for translating medical images from noisy data
Wentao Chen, Xichen Xu, Jie Luo, Weimin Zhou
SPIE Medical Imaging 2024: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Unsupervised generation of pseudo normal PET from MRI with diffusion model for epileptic focus localization
Wentao Chen, Jiwei Li, Xichen Xu, Hui Huang, Siyu Yuan, Miao Zhang, Tianming Xu, Jie Luo, Weimin Zhou
SPIE Medical Imaging 2024: Clinical and Biomedical Engineering
[Paper]
2023
Approximating the Hotelling observer with autoencoder-learned efficient channels for binary signal detection tasks
Jason L Granstedt, Weimin Zhou, Mark A Anastasio
Journal of Medical Imaging
[Paper]
Estimating task-based performance bounds for image reconstruction methods by use of learned-ideal observers
Kaiyan Li, Weimin Zhou, Hua Li, Mark A Anastasio
SPIE Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Task-aware denoising autoencoders for establishing efficient channels
Weimin Zhou
SPIE Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Optimal visual search strategy with inter-saccade response correlations
Weimin Zhou, Miguel P Eckstein
SPIE Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Ideal Observer Computation by Use of Markov-Chain Monte Carlo with Generative Adversarial Networks
Weimin Zhou, Umberto Villa, Mark A Anastasio
IEEE Transactions on Medical Imaging
[Paper]
2022
Ideal Searcher with Inter-Saccade Response Correlations
Weimin Zhou, Miguel P Eckstein
Journal of Vision
[Paper]
Analyzing neural networks applied to an anatomical simulation of the breast
Craig K Abbey, Sourya Sengupta, Weimin Zhou, Andreu Badal, Rongping Zeng, Frank W Samuelson, Miguel P Eckstein, Kyle J Myers, Mark A Anastasio, Jovan G Brankov
SPIE Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment
[Paper]
A deep Q-learning method for optimizing visual search strategies in backgrounds of dynamic noise
Weimin Zhou, Miguel P Eckstein
SPIE Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Learning stochastic object models from medical imaging measurements by use of advanced ambient generative adversarial networks
Weimin Zhou, Sayantan Bhadra, Frank J Brooks, Hua Li, Mark A Anastasio
Journal of Medical Imaging
[Paper]
2021
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
Kaiyan Li, Weimin Zhou, Hua Li, Mark A Anastasio
IEEE Transactions on Medical Imaging
[Paper]
A signal detection model for quantifying overregularization in nonlinear image reconstruction
Emil Y Sidky, John Paul Phillips, Weimin Zhou, Greg Ongie, Juan P Cruz‐Bastida, Ingrid S Reiser, Mark A Anastasio, Xiaochuan Pan
Medical Physics
[Paper]
Assessing the Impact of Deep Neural Network-based Image Denoising on Binary Signal Detection Tasks
Kaiyan Li, Weimin Zhou, Hua Li, Mark A Anastasio
IEEE Transactions on Medical Imaging
[Paper]
Supervised learning-based ideal observer approximation for joint detection and estimation tasks
Kaiyan Li, Weimin Zhou, Hua Li, Mark A Anastasio
Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Task-based performance evaluation of deep neural network-based image denoising
Kaiyan Li, Weimin Zhou, Hua Li, Mark A Anastasio
Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment
[Paper]
A hybrid channelized Hotelling observer for estimating the ideal linear observer for total-variation-based image reconstruction
John Paul Phillips, Emil Y Sidky, Greg Ongie, Weimin Zhou, Juan P Cruz-Bastida, Ingrid S Reiser, Mark A Anastasio, Xiaochuan Pan
SPIE Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment
[Paper]
SlabGAN: a method for generating efficient 3D anisotropic medical volumes using generative adversarial networks
Jason L Granstedt, Varun A Kelkar, Weimin Zhou, Mark A Anastasio
Medical Imaging 2021: Image Processing
[Paper]
Advancing the AmbientGAN for learning stochastic object models
Weimin Zhou, Sayantan Bhadra, Frank J Brooks, Jason L Granstedt, Hua Li, Mark A Anastasio
SPIE Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment
[Paper]
2020
Developing signal detectability as an image quality metric for use with non-linear image reconstruction
Emil Y Sidky, Weimin Zhou, Greg Ongie, Juan P Cruz-Bastida, Ingrid S Reiser, Mark A Anastasio, Xiaochuan Pan
The 6th International Conference on Image Formation in X-Ray Computed Tomography
[Paper]
Approximating the ideal observer for joint signal detection and localization tasks by use of supervised learning methods
Weimin Zhou, Hua Li, Mark A Anastasio
IEEE Transactions on Medical Imaging
[Paper]
Quantitative Performance Analysis of Supervised Transfer Learning and Unsupervised Domain Adaptation Methods Employed in Medical Imaging Applications
Shenghua He, Weimin Zhou, Kaiyan Li, Mark A Anastasio, Hua Li
2020 Joint AAPM/COMP Meeting
[Paper]
Supervised Learning-Based Ideal Observer Approximation for Joint Detection and Estimation Tasks
Kaiyan Li, Weimin Zhou, Shenghua He, Hua Li, Mark A Anastasio
2020 Joint AAPM/COMP Meeting
[Paper]
Learning stochastic object models from medical imaging measurements using Progressively-Growing AmbientGANs
Weimin Zhou, Sayantan Bhadra, Frank J Brooks, Hua Li, Mark A Anastasio
arXiv preprint arXiv:2006.00033
[Paper]
Learning efficient channels with a dual loss autoencoder
Jason L Granstedt, Weimin Zhou, Mark A Anastasio
Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Learning numerical observers using unsupervised domain adaptation
Shenghua He, Weimin Zhou, Hua Li, Mark A Anastasio
Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Medical image reconstruction with image-adaptive priors learned by use of generative adversarial networks
Sayantan Bhadra, Weimin Zhou, Mark A Anastasio
Medical Imaging 2020: Physics of Medical Imaging
[Paper]
Markov-chain monte carlo approximation of the ideal observer using generative adversarial networks
Weimin Zhou, Mark A Anastasio
Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements
Weimin Zhou, Sayantan Bhadra, Frank J Brooks, Hua Li, Mark A Anastasio
Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Approximating the Hotelling Observer with Autoencoder-Learned Efficient Channels for Binary Signal Detection Tasks
Jason L Granstedt, Weimin Zhou, Mark A Anastasio
arXiv preprint arXiv:2003.02321
[Paper]
X-ray CT in phase contrast enhancement geometry of alginate microbeads in a whole-animal model
Jacob Brown, Sami Somo, Frank Brooks, Sergey Komarov, Weimin Zhou, Mark Anastasio, Eric Brey
Annals of biomedical engineering
[Paper]
Comparison of data-acquisition designs for single-shot edge-illumination X-ray phase-contrast tomography
Yujia Chen, Weimin Zhou, Charlotte K Hagen, Alessandro Olivo, Mark A Anastasio
Optics Express
[Paper]
2019
Approximating the ideal observer and hotelling observer for binary signal detection tasks by use of supervised learning methods
Weimin Zhou, Hua Li, Mark A Anastasio
IEEE Transactions on Medical Imaging
[Paper]
Learning the ideal observer for joint detection and localization tasks by use of convolutional neural networks
Weimin Zhou, Mark A Anastasio
Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Learning stochastic object model from noisy imaging measurements using AmbientGANs
Weimin Zhou, Sayantan Bhadra, Frank Brooks, Mark A Anastasio
Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Learning the Hotelling observer for SKE detection tasks by use of supervised learning methods
Weimin Zhou, Hua Li, Mark A Anastasio
Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment
[Paper]
Autoencoder embedding of task-specific information
Jason L Granstedt, Weimin Zhou, Mark A Anastasio
Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment
[Paper]
X-ray Phase Contrast Imaging of Soft Biomaterials in a Whole-Animal Model
Jacob Brown, Sami Somo, Frank Brooks, Sergey Komarov, Weimin Zhou, Mark Anastasio, Eric Brey
42nd Society for Biomaterials Annual Meeting and Exposition 2019: The Pinnacle of Biomaterials Innovation and Excellence
[Paper]
2018
Development of computed phase-sensitive x-ray imaging technologies for pre-clinical science (Conference Presentation)
Mark A Anastasio, Frank Brooks, Sergey Komarov, Yujia Chen, Weimin Zhou
Anomaly Detection and Imaging with X-Rays (ADIX) III
[Paper]
Joint-reconstruction-enabled data acquisition design for single-shot edge-illumination x-ray phase-contrast tomography
Yujia Chen, Weimin Zhou, Mark A Anastasio
Medical Imaging 2018: Physics of Medical Imaging
[Paper]
Learning the ideal observer for SKE detection tasks by use of convolutional neural networks (Cum Laude Poster Award)
Weimin Zhou, Mark A Anastasio
Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment
[Paper]
2017
Generation of anatomically realistic numerical phantoms for photoacoustic and ultrasonic breast imaging
Yang Lou, Weimin Zhou, Thomas P Matthews, Catherine M Appleton, Mark A Anastasio
Journal of Biomedical Optics
[Paper]