Learning stochastic object models from medical imaging measurements by use of advanced ambient generative adversarial networks is a research paper published in Journal of Medical Imaging (2022). On theSindex it has a DataRank of 0. It has been cited 14 times.
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NIBIB NIH HHS
Grant: R01 EB028652
NINDS NIH HHS
Grant: R01 NS102213
NIBIB NIH HHS
Grant: R01 EB020604
NIA NIH HHS
Grant: U01 AG024904
NIBIB NIH HHS
Grant: R01 EB023045
National Institutes of Health
Grant: 1R01EB023045-01A1
DEVELOPMENT OF A RAPID METHOD FOR IMAGING REGIONAL VENTILATION IN SMALL ANIMALS W/O CONTRAST AGENTS
National Institutes of Health
Grant: 5R01EB028652-04
Advanced image reconstruction for accurate and high-resolution breast ultrasound tomography
National Institutes of Health
Grant: 1U01AG024904-01
Alzheimers Disease Neuroimaging Initiative
National Institutes of Health
Grant: 5R01NS102213-03
Safe, rapid & functional pediatric brain imaging using photoacoustic computed tomography
FWCI
1.06
Citation Percentile
0.8%
Citation Trend
Fields of Study
Keywords
Learning stochastic object models from medical imaging measurements by use of advanced ambient generative adversarial networks