Bayesian Posterior Distribution Estimation of Kinetic Parameters in Dynamic Brain PET Using Generative Deep Learning Models

Positron Emission Tomography (PET) is a valuable imaging method for studying molecular-level processes in the body, such as hyperphosphorylated tau (ptau) protein aggregates, a hallmark of several neurodegenerative diseases including Alzheimer's disease. P-tau density and cerebral perfusion can...

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Veröffentlicht in:	IEEE transactions on medical imaging Jg. PP; S. 1
Hauptverfasser:	Djebra, Yanis, Liu, Xiaofeng, Marin, Thibault, Tiss, Amal, Dhaynaut, Maeva, Guehl, Nicolas, Johnson, Keith, Fakhri, Georges El, Ma, Chao, Ouyang, Jinsong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 15.07.2025
Schlagworte:	Conditional Variational Autoencoder Data models Deep learning Diffusion models Diffusion processes Dynamic PET imaging Estimation Imaging Kinetic modeling Kinetic theory Noise Positron emission tomography Posterior distribution Radiotracer Training
ISSN:	0278-0062, 1558-254X, 1558-254X
Online-Zugang:	Volltext
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