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تراکتوگرافی DTI×مدل‌سازی کینتیک PET×
حوزهتصویربرداری پزشکیتصویربرداری پزشکی
خانوادهProcess / pipelineProcess / pipeline
سال پیدایش19991983
پدیدآورPeter BasserChristoph Patlak
نوعFiber tracking from diffusion MRIMathematical framework for tracer kinetics in PET imaging
منبع بنیادینBasser, 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 ↗
نام‌های دیگرDiffusion tensor tractography, White matter tractography, Fiber trackingPET pharmacokinetics, Dynamic PET, PET compartmental modeling
مرتبط55
خلاصهDiffusion 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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ScholarGateمقایسهٔ روش‌ها: DTI Tractography · PET Kinetic Modeling. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare