Linganisha mbinu

	Takwimu za Kianzio-Njia za Spesho (TBSS)	Picha ya Kurtosis ya Usambazaji	Mofometria Inayotegemea Vokseli
Nyanja	Upigaji Picha wa Ubongo	Upigaji Picha wa Ubongo	Upigaji Picha wa Ubongo
Familia	Process / pipeline	Process / pipeline	Process / pipeline
Mwaka wa asili	2006	2005	2000
Mwanzilishi	Stephen M. Smith	Jens Jensen	John Ashburner
Aina	Diffusion MRI white matter analysis pipeline	Microstructural white matter analysis	Structural MRI gray matter analysis pipeline
Chanzo asilia	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.	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.	Ashburner, J., & Friston, K. J. (2000). Voxel-based morphometry—the methods. NeuroImage, 11(6), 805–821.
Majina mbadala	TBSS, white matter skeleton analysis	DKI, non-Gaussian diffusion, diffusion kurtosis	VBM, grey matter morphometry
Zinazohusiana	3	3	2
Muhtasari	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.	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.	Voxel-Based Morphometry (VBM) is a whole-brain statistical technique for detecting local differences in gray matter volume or concentration from structural MRI. Introduced by John Ashburner and Karl Friston in 2000, VBM enables researchers to identify regional brain volume changes associated with disease, aging, learning, and other factors without requiring a priori region-of-interest definitions.