Automation of cross-sectional analysis of neuroimages using diffusion kurtosis imaging

Recent advances in magnetic resonance imaging allow quantification of diffusion of water molecules, through diffusion weighted magnetic resonance images(DW-MRI)techniques called diffusion tensor imaging(DTI) and diffusion kurtosis imaging( DKI). These techniques are being extensively used to study finer details of the micro-structure in the human brain. Inspite of availability of several software packages for DW-MRI analysis, not many are available for estimating DKI. An easy to use and fully automated processing of DW-MRI for estimation and analysis of DKI is still lacking. In this paper, we describe the development of a MATLAB toolbox which facilitates estimation, display and cross-sectional analysis of brain images using DKI by fully automating the DKI analysis pipeline, right from initial data loading till performing statistical analysis with an user friendly graphical user interface(GUI). The major functionalities which are integrated in this toolbox includes diffusion data preprocessing, estimation of diffusion tensor and diffusion kurtosis metrics, displaying parametric maps and statistical analysis of diffusion metrics for cross sectional brain studies. The functionalities and performance of the toolbox has been extensively evaluated with multiple DW-MRI datasets acquired from normal subjects achieving very promising results. The capabilities of the toolbox are demonstrated by conducting in-vivo DKI studies for analysing the aging effects.