方法对比

	磁化传递比	神经元定向扩散与密度成像 (NODDI)	基于纤维束的空间统计
领域	神经影像	神经影像	神经影像
方法族	Process / pipeline	Process / pipeline	Process / pipeline
起源年份	1989	2012	2006
提出者	Stephen Wolff	Hui Zhang	Stephen M. Smith
类型	Tissue microstructure characterization	Microstructural white matter mapping	Diffusion MRI white matter analysis pipeline
开创性文献	Wolff, S. D., & Balaban, R. S. (1989). Magnetization transfer contrast (MTC) and tissue water proton relaxation in vivo. Journal of Magnetic Resonance Imaging, 10(2), 135–148.	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.
别名	MTR, magnetization transfer, MT imaging	NODDI, neurite density mapping	TBSS, white matter skeleton analysis
相关	3	3	3
摘要	Magnetisation Transfer Ratio (MTR) is an MRI method that measures the exchange of magnetization between free water protons and protons bound to macromolecules (primarily myelin lipids and proteins). Introduced by Wolff and Balaban in 1989, MTR reflects tissue macromolecular content and is particularly sensitive to myelination, providing a non-invasive estimate of myelin density.	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.