Approximating the ideal observer for joint signal detection and estimation tasks by the use of Markov-Chain Monte Carlo with generative adversarial networks
By combining GAN-based generative modeling with MCMC, the hybrid MCMC-GAN method extends a previously proposed IO approximation method to more general detection-estimation tasks. This provides a new capability to benchmark and optimize imaging-system performance through virtual imaging studies.
Authors
- Weimin Zhou (ORCID: https://orcid.org/0000-0001-6678-4088)
- Mark A. Anastasio (ORCID: https://orcid.org/0000-0002-3192-4172)
- Dan Li (ORCID: https://orcid.org/0000-0001-6735-6181)
- Kaiyan Li (ORCID: https://orcid.org/0000-0003-3608-590X)
Institutions
- University of Arizona (US)
- University of Illinois Urbana-Champaign (US)
Publication Details
- Journal
- Journal of Medical Imaging
- Published
- 2025-10-21
- DOI
- https://doi.org/10.1117/1.jmi.12.5.051810
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00