DTI-Statistics FRATS Toolkit
Introduction
FRATS: Functional Regression Analysis of DTI Tract Statistics a functional regression framework, is for the analysis of multiple diffusion properties along fiber bundle as functions in an infinite dimensional space and their association with a set of covariates of interest, such as age, diagnostic status and gender, in real applications. It consists of four integrated components: the local polynomial kernel method for smoothing multiple diffusion properties along individual fiber bundles, a functional linear model for characterizing the association between fiber bundle diffusion properties and a set of covariates, a global test statistic for testing hypotheses of interest, and a resampling method for approximating the p-value of the global test statistic. The resulting analysis pipeline can be used for understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of environmental and genetic factors on white matter fiber bundles.
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References
1. Zhu, H. T., Styner, M., Tang, N. S., Liu, Z. X., Lin, W. L., and Gilmore, J. (2010). "FRATS: Functional Regression Analysis of DTI Tract Statistics", IEEE Transactions on Medical Imaging, 29:1039 - 1049.[pdf]