Weimin Zhou

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 42

Top Topics

Medical Imaging

Convolutional Neural Networks

Top Venues

Medical Imaging: Image Perception, Observer Performance, and Technology Assessment

IEEE Trans. Medical Imaging

Publications

Ruotong Li, Weimin Zhou
Image Super-Resolution Reconstruction of Landslide Based on Real-ESRGAN. CCEAI (2024)
Wentao Chen, Xichen Xu, Jie Luo, Weimin Zhou
Ambient-Pix2PixGAN for Translating Medical Images from Noisy Data. CoRR (2024)
Xichen Xu, Wentao Chen, Weimin Zhou
AmbientCycleGAN for Establishing Interpretable Stochastic Object Models Based on Mathematical Phantoms and Medical Imaging Measurements. CoRR (2024)
Wentao Chen, Jiwei Li, Xichen Xu, Hui Huang, Siyu Yuan, Miao Zhang, Tianming Xu, Jie Luo, Weimin Zhou
Unsupervised Generation of Pseudo Normal PET from MRI with Diffusion Model for Epileptic Focus Localization. CoRR (2024)
Weimin Zhou, Umberto Villa, Mark A. Anastasio
Ideal Observer Computation by Use of Markov-Chain Monte Carlo With Generative Adversarial Networks. IEEE Trans. Medical Imaging 42 (12) (2023)
Weimin Zhou
Image Dehazing Enhancement Algorithm Based on Mean Guided Filtering. J. Inf. Process. Syst. 19 (4) (2023)
Weimin Zhou
Task-aware denoising autoencoders for establishing efficient channels. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2023)
Weimin Zhou, Umberto Villa, Mark A. Anastasio
Ideal Observer Computation by Use of Markov-Chain Monte Carlo with Generative Adversarial Networks. CoRR (2023)
Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio
Estimating task-based performance bounds for image reconstruction methods by use of learned-ideal observers. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2023)
Weimin Zhou, Miguel P. Eckstein
Optimal visual search strategy with inter-saccade response correlations. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2023)
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
Analyzing neural networks applied to an anatomical simulation of the breast. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2022)
Kaiyan Li, Weimin Zhou, Hua Li, Mark 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. Medical Imaging 41 (5) (2022)
Weimin Zhou, Miguel P. Eckstein
A deep Q-learning method for optimizing visual search strategies in backgrounds of dynamic noise. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2022)
Weimin Zhou, Miguel P. Eckstein
A deep Q-learning method for optimizing visual search strategies in backgrounds of dynamic noise. CoRR (2022)
Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Jason L. Granstedt, Hua Li, Mark A. Anastasio
Advancing the AmbientGAN for learning stochastic object models. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2021)
Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio
Supervised learning-based ideal observer approximation for joint detection and estimation tasks. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2021)
Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio
Task-based performance evaluation of deep neural network-based image denoising. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2021)
Jason L. Granstedt, Varun A. Kelkar, Weimin Zhou, Mark A. Anastasio
SlabGAN: a method for generating efficient 3D anisotropic medical volumes using generative adversarial networks. Medical Imaging: Image Processing (2021)
Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Jason L. Granstedt, Hua Li, Mark A. Anastasio
Advancing the AmbientGAN for learning stochastic object models. CoRR (2021)
Yun Liu, Hao Liu, Zhen-Guo Fu, Weimin Zhou
Increase in Axial Compressibility in a Spinning Van der Waals Gas. Entropy 23 (2) (2021)
Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio
Learning stochastic object models from medical imaging measurements by use of advanced AmbientGANs. CoRR (2021)
John Paul Phillips, Emil Y. Sidky, Greg Ongie, Weimin Zhou, Juan-Pablo Cruz-Bastida, Ingrid S. Reiser, Mark A. Anastasio, Xiaochuan Pan
A hybrid channelized Hotelling observer for estimating the ideal linear observer for total-variation-based image reconstruction. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2021)
Kaiyan Li, Weimin Zhou, Hua Li, Mark A. Anastasio
Assessing the Impact of Deep Neural Network-Based Image Denoising on Binary Signal Detection Tasks. IEEE Trans. Medical Imaging 40 (9) (2021)
Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio
Progressively-Growing AmbientGANs For Learning Stochastic Object Models From Imaging Measurements. CoRR (2020)
Shenghua He, Weimin Zhou, Hua Li, Mark A. Anastasio
Learning numerical observers using unsupervised domain adaptation. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2020)
Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio
Learning efficient channels with a dual loss autoencoder. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2020)
Sayantan Bhadra, Weimin Zhou, Mark A. Anastasio
Medical image reconstruction with image-adaptive priors learned by use of generative adversarial networks. CoRR (2020)
Weimin Zhou, Mark A. Anastasio
Markov-Chain Monte Carlo Approximation of the Ideal Observer using Generative Adversarial Networks. CoRR (2020)
Shenghua He, Weimin Zhou, Hua Li, Mark A. Anastasio
Learning Numerical Observers using Unsupervised Domain Adaptation. CoRR (2020)
Weimin Zhou, Hua Li, Mark A. Anastasio
Approximating the Ideal Observer for joint signal detection and localization tasks by use of supervised learning methods. CoRR (2020)
Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio
Learning stochastic object models from medical imaging measurements using Progressively-Growing AmbientGANs. CoRR (2020)
Weimin Zhou, Hua Li, Mark A. Anastasio
Approximating the Ideal Observer for Joint Signal Detection and Localization Tasks by use of Supervised Learning Methods. IEEE Trans. Medical Imaging 39 (12) (2020)
Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio
Approximating the Hotelling Observer with Autoencoder-Learned Efficient Channels for Binary Signal Detection Tasks. CoRR (2020)
Weimin Zhou, Mark A. Anastasio
Markov-Chain Monte Carlo approximation of the Ideal Observer using generative adversarial networks. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2020)
Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Hua Li, Mark A. Anastasio
Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2020)
Weimin Zhou, Hua Li, Mark A. Anastasio
Learning the Hotelling observer for SKE detection tasks by use of supervised learning methods. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2019)
Weimin Zhou, Sayantan Bhadra, Frank J. Brooks, Mark A. Anastasio
Learning stochastic object model from noisy imaging measurements using AmbientGANs. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2019)
Weimin Zhou, Mark A. Anastasio
Learning the ideal observer for joint detection and localization tasks by use of convolutional neural networks. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2019)
Weimin Zhou, Hua Li, Mark A. Anastasio
Approximating the Ideal Observer and Hotelling Observer for binary signal detection tasks by use of supervised learning methods. CoRR (2019)
Weimin Zhou, Hua Li, Mark A. Anastasio
Approximating the Ideal Observer and Hotelling Observer for Binary Signal Detection Tasks by Use of Supervised Learning Methods. IEEE Trans. Medical Imaging 38 (10) (2019)
Jason L. Granstedt, Weimin Zhou, Mark A. Anastasio
Autoencoder embedding of task-specific information. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2019)
Weimin Zhou, Mark A. Anastasio
Learning the ideal observer for SKE detection tasks by use of convolutional neural networks. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2018)