Learning stochastic object models from medical imaging measurements by use of advanced ambient generative adversarial networks

PURPOSE: To objectively assess new medical imaging technologies via computer-simulations, it is important to account for the variability in the ensemble of objects to be imaged. This source of variability can be described by stochastic object models (SOMs). It is generally desirable to establish SOM...

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Detalles Bibliográficos
Autores principales: Zhou, Weimin, Bhadra, Sayantan, Brooks, Frank J., Li, Hua, Anastasio, Mark A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2022
Materias:
Image Perception, Observer Performance, and Technology Assessment
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866417/
https://www.ncbi.nlm.nih.gov/pubmed/35229009
http://dx.doi.org/10.1117/1.JMI.9.1.015503

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866417/
https://www.ncbi.nlm.nih.gov/pubmed/35229009
http://dx.doi.org/10.1117/1.JMI.9.1.015503

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