Compara mètodes

	NODDI	Imatge de Kurtosi de Difusió	Estadística Espacial Basada en Tractes
Camp	Neuroimatge	Neuroimatge	Neuroimatge
Família	Process / pipeline	Process / pipeline	Process / pipeline
Any d'origen	2012	2005	2006
Autor original	Hui Zhang	Jens Jensen	Stephen M. Smith
Tipus	Microstructural white matter mapping	Microstructural white matter analysis	Diffusion MRI white matter analysis pipeline
Font seminal	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.	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.	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.
Àlies	NODDI, neurite density mapping	DKI, non-Gaussian diffusion, diffusion kurtosis	TBSS, white matter skeleton analysis
Relacionats	3	3	3
Resum	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.	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.	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.