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DTI Tractography×PET kinētiskā modelēšana×
NozareMedicīniskā attēlveidošanaMedicīniskā attēlveidošana
SaimeProcess / pipelineProcess / pipeline
Izcelsmes gads19991983
AutorsPeter BasserChristoph Patlak
TipsFiber tracking from diffusion MRIMathematical framework for tracer kinetics in PET imaging
PirmavotsBasser, P. J., Mattiello, J., LeBihan, D. (1994). Estimation of the effective self-diffusion tensor from the NMR spin echo. Journal of Magnetic Resonance, Series B, 103(3), 247-254. DOI ↗Patlak, C. S., Blasberg, R. G., Fenstermacher, J. D. (1983). Graphical evaluation of blood-to-brain transfer constants from multiple-time uptake data. Journal of Cerebral Blood Flow & Metabolism, 3(1), 1-7. DOI ↗
Citi nosaukumiDiffusion tensor tractography, White matter tractography, Fiber trackingPET pharmacokinetics, Dynamic PET, PET compartmental modeling
Saistītās55
KopsavilkumsDiffusion Tensor Imaging Tractography (DTI tractography) is a non-invasive neuroimaging technique that maps white matter fiber bundles in the brain by tracking the three-dimensional diffusion of water molecules along axons. Pioneered by Basser, Mori, and Conturo in the 1990s, DTI tractography reveals the structural connectivity of the brain, enabling visualization of major pathways (corpus callosum, arcuate fasciculus, corticospinal tract) and assessment of fiber integrity. It is widely used in neurosurgical planning, neurological disease assessment, and brain connectivity research.PET kinetic modeling is a quantitative analysis technique that tracks the temporal behavior of radioactive tracers in tissue to extract physiological parameters such as blood flow, metabolic rate, and receptor density. Established by Patlak, Logan, and Gunn in the 1980s and 1990s, kinetic modeling transforms raw PET time-activity curves into interpretable biological measures. It is widely used in neurology, oncology, and cardiology to assess disease severity, treatment response, and regional tissue function.
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ScholarGateSalīdzināt metodes: DTI Tractography · PET Kinetic Modeling. Izgūts 2026-06-19 no https://scholargate.app/lv/compare