विधियों की तुलना करें

	विसरण कर्टोसिस इमेजिंग	NODDI	ट्रैक्ट-आधारित स्थानिक सांख्यिकी
क्षेत्र	तंत्रिका प्रतिबिंबन	तंत्रिका प्रतिबिंबन	तंत्रिका प्रतिबिंबन
परिवार	Process / pipeline	Process / pipeline	Process / pipeline
उद्भव वर्ष	2005	2012	2006
प्रवर्तक	Jens Jensen	Hui Zhang	Stephen M. Smith
प्रकार	Microstructural white matter analysis	Microstructural white matter mapping	Diffusion MRI white matter analysis pipeline
मौलिक स्रोत	Jensen, J. H., Helpern, J. A., Ramani, A., et al. (2005). Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by magnetic resonance imaging. Magnetic Resonance in Medicine, 53(6), 1432–1440.	Zhang, H., Schneider, T., Wheeler-Kingshott, C. A., & Alexander, D. C. (2012). NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. NeuroImage, 61(4), 1000–1016.	Smith, S. M., Jenkinson, M., Johansen-Berg, H., et al. (2006). Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. NeuroImage, 31(4), 1487–1505.
उपनाम	DKI, non-Gaussian diffusion, diffusion kurtosis	NODDI, neurite density mapping	TBSS, white matter skeleton analysis
संबंधित	3	3	3
सारांश	Diffusion Kurtosis Imaging (DKI) is an advanced diffusion MRI technique that quantifies non-Gaussian diffusion of water molecules, providing detailed information about tissue microstructure beyond conventional diffusion tensor imaging. Introduced by Jensen and colleagues in 2005, DKI detects deviations from normal Gaussian diffusion, revealing information about cellular compartmentalization and fiber heterogeneity.	Neurite Orientation Dispersion and Density Imaging (NODDI) is a biophysical diffusion MRI model that quantifies microstructural properties of white matter: neurite density (axonal density), orientation dispersion (fiber coherence), and isotropic diffusion (free water or cerebrospinal fluid). Introduced by Zhang and colleagues in 2012, NODDI provides biologically interpretable metrics directly linking diffusion MRI signals to tissue microstructure.	Tract-Based Spatial Statistics (TBSS) is a voxel-wise analysis method for detecting group differences in white matter microstructure from diffusion MRI data. Published by Stephen M. Smith and colleagues in 2006, TBSS addresses registration and multiple comparison problems inherent in voxel-wise analysis by projecting individual FA maps onto a white matter skeleton derived from a population template.