Survey on sampling conditioned brain images and imaging measures with generative models

Generative models have become innovative tools across various domains, including neuroscience, where they enable the synthesis of realistic brain imaging data that captures complex anatomical and functional patterns. These models, such as Variational Autoencoders (VAEs), Generative Adversarial Netwo...

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Vydané v:	Biomedical engineering letters Ročník 15; číslo 5; s. 831 - 843
Hlavní autori:	Cheong, Sehyoung, Lee, Hoseok, Kim, Won Hwa
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Korea The Korean Society of Medical and Biological Engineering 01.09.2025 Springer Nature B.V
Predmet:	Biological and Medical Physics Biomedical Engineering and Bioengineering Biomedicine Biophysics Brain Brain research Conditioning Data acquisition Datasets Deep learning Diffusion models Disease Engineering Generative adversarial networks Genetic factors Image quality Learning Machine learning Medical and Radiation Physics Medical imaging Nervous system Neural networks Neuroimaging Neurosciences Phenotypes Review Article Synthetic data Variables Conditional generation Brain imaging VAE GAN Diffusion model
ISSN:	2093-9868, 2093-985X, 2093-985X
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