| Generation of anatomically realistic numerical phantoms for photoacoustic and ultrasonic breast imaging Y Lou, W Zhou, TP Matthews, CM Appleton, MA Anastasio Journal of biomedical optics 22 (4), 041015-041015, 2017 | 95 | 2017 |
| Approximating the ideal observer and hotelling observer for binary signal detection tasks by use of supervised learning methods W Zhou, H Li, MA Anastasio IEEE transactions on medical imaging 38 (10), 2456-2468, 2019 | 71 | 2019 |
| Assessing the Impact of Deep Neural Network-based Image Denoising on Binary Signal Detection Tasks K Li, W Zhou, H Li, MA Anastasio IEEE Transactions on Medical Imaging 40 (9), 2295-2305, 2021 | 55 | 2021 |
| Medical image reconstruction with image-adaptive priors learned by use of generative adversarial networks S Bhadra, W Zhou, MA Anastasio Medical imaging 2020: physics of medical imaging 11312, 206-213, 2020 | 33 | 2020 |
| Approximating the ideal observer for joint signal detection and localization tasks by use of supervised learning methods W Zhou, H Li, MA Anastasio IEEE transactions on medical imaging 39 (12), 3992-4000, 2020 | 28 | 2020 |
| Markov-chain monte carlo approximation of the ideal observer using generative adversarial networks W Zhou, MA Anastasio Medical Imaging 2020: Image Perception, Observer Performance, and Technology …, 2020 | 23 | 2020 |
| Learning the ideal observer for SKE detection tasks by use of convolutional neural networks (Cum Laude Poster Award) W Zhou, MA Anastasio Medical Imaging 2018: Image Perception, Observer Performance, and Technology …, 2018 | 23 | 2018 |
| Learning stochastic object models from medical imaging measurements by use of advanced ambient generative adversarial networks W Zhou, S Bhadra, FJ Brooks, H Li, MA Anastasio Journal of Medical Imaging 9 (1), 015503-015503, 2022 | 17* | 2022 |
| Learning the Hotelling observer for SKE detection tasks by use of supervised learning methods W Zhou, H Li, MA Anastasio Medical Imaging 2019: Image Perception, Observer Performance, and Technology …, 2019 | 17 | 2019 |
| 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 K Li, W Zhou, H Li, MA Anastasio IEEE transactions on medical imaging 41 (5), 1114-1124, 2021 | 13 | 2021 |
| Task-based performance evaluation of deep neural network-based image denoising K Li, W Zhou, H Li, MA Anastasio Medical Imaging 2021: Image Perception, Observer Performance, and Technology …, 2021 | 12 | 2021 |
| Supervised learning-based ideal observer approximation for joint detection and estimation tasks K Li, W Zhou, H Li, MA Anastasio Medical Imaging 2021: Image Perception, Observer Performance, and Technology …, 2021 | 11 | 2021 |
| A signal detection model for quantifying overregularization in nonlinear image reconstruction EY Sidky, JP Phillips, W Zhou, G Ongie, JP CruzBastida, IS Reiser, ... Medical physics 48 (10), 6312-6323, 2021 | 10 | 2021 |
| Learning the ideal observer for joint detection and localization tasks by use of convolutional neural networks W Zhou, MA Anastasio Medical Imaging 2019: Image Perception, Observer Performance, and Technology …, 2019 | 10 | 2019 |
| Learning stochastic object model from noisy imaging measurements using AmbientGANs W Zhou, S Bhadra, F Brooks, MA Anastasio Medical Imaging 2019: Image Perception, Observer Performance, and Technology …, 2019 | 10 | 2019 |
| Learning numerical observers using unsupervised domain adaptation S He, W Zhou, H Li, MA Anastasio Medical Imaging 2020: Image Perception, Observer Performance, and Technology …, 2020 | 9 | 2020 |
| Progressively-Growing AmbientGANs for learning stochastic object models from imaging measurements W Zhou, S Bhadra, FJ Brooks, H Li, MA Anastasio Medical Imaging 2020: Image Perception, Observer Performance, and Technology …, 2020 | 7 | 2020 |
| Learning stochastic object models from medical imaging measurements using Progressively-Growing AmbientGANs W Zhou, S Bhadra, FJ Brooks, H Li, MA Anastasio arXiv preprint arXiv:2006.00033, 2020 | 6 | 2020 |
| SlabGAN: a method for generating efficient 3D anisotropic medical volumes using generative adversarial networks JL Granstedt, VA Kelkar, W Zhou, MA Anastasio Medical Imaging 2021: Image Processing 11596, 329-335, 2021 | 5 | 2021 |
| Advancing the AmbientGAN for learning stochastic object models W Zhou, S Bhadra, FJ Brooks, JL Granstedt, H Li, MA Anastasio Medical Imaging 2021: Image Perception, Observer Performance, and Technology …, 2021 | 5 | 2021 |
Mark A. AnastasioUniversity of Illinois Urbana-Champaign在 illinois.edu 的电子邮件经过验证
