FADTTS: Functional Analysis of Diffusion Tensor Tract Statistics, a DTI-Statistics Toolkit
FADTTS is a functional analysis pipeline for delineating the structure of the variability of multiple di usion properties along major white matter fiber bundles and their association with a set of covariates of interest, such as age, diagnostic status and gender, in various diffiusion tensor imaging studies. The FADTTS integrates five statistical tools: a multivariate varying coefficient model for allowing the varying coefficient functions to characterize the varying association between fiber bundles di union properties and a set of covariates, a weighted least squares estimation to estimate the varying coefficient functions, a functional principal component analysis to delineate the structure of the variability in fiber bundles diffusion properties, a global test statistic to test hypotheses of interest, and a simultaneous conffidence band to quantify the uncertainty in the estimated coefficient function. FADTTS can be used to facilitate understanding normal brain development, the neural bases of neuropsychiatric disorders, and the joint effects of
environmental and genetic factors on white matter fiber bundles.
Software Download (with GUI) & Supplementary Documents
Citation:
1. Zhu H, Li R, and Kong L. Multivariate varying coefficient models for functional responses. Annals of Statistics. 2012.
2. Zhu H, Kong L, Li R, et al. FADTTS: functional analysis of diffusion tensor tract statistics. Neuroimage. 2011.
3. Zhu H, Styner M, Li Y, et al. Multivariate varying coefficient models for DTI tract statistics. Med Image Comput Comput Assist Interv. 2010.
4. Verde AR, Berger JB, Gupta A, et al. UNC-Utah NA-MIC DTI framework: Atlas Based Fiber Tract Analysis with Application to a Study of Nicotine Smoking Addiction. Proc SPIE Int Soc Opt Eng. 2013.