dMRI can be used to quantify white matter (WM) property and to virtually reconstruct WM pathways in the living brain ( Le Bihan, 2003). This novel toolbox is expected to substantially simplify the image processing of dMRI datasets and facilitate human structural connectome studies.ĭiffusion magnetic resonance imaging (dMRI) has become one of the most popular MRI techniques for brain research. As an open-source package, PANDA is freely available at. In addition, PANDA has a friendly graphical user interface (GUI), allowing the user to be interactive and to adjust the input/output settings, as well as the processing parameters. In particular, PANDA can process different subjects in parallel, using multiple cores either in a single computer or in a distributed computing environment, thus greatly reducing the time cost when dealing with a large number of datasets.
#Pipeline toolbox series#
Using any number of raw dMRI datasets from different subjects, in either DICOM or NIfTI format, PANDA can automatically perform a series of steps to process DICOM/NIfTI to diffusion metrics that are ready for statistical analysis at the voxel-level, the atlas-level and the Tract-Based Spatial Statistics (TBSS)-level and can finish the construction of anatomical brain networks for all subjects.
#Pipeline toolbox software#
The processing modules of a few established packages, including FMRIB Software Library (FSL), Pipeline System for Octave and Matlab (PSOM), Diffusion Toolkit and MRIcron, were employed in PANDA.
Here, we developed a MATLAB toolbox named “Pipeline for Analyzing braiN Diffusion imAges” (PANDA) for fully automated processing of brain diffusion images. While a number of post-processing packages have been developed, fully automated processing of dMRI datasets remains challenging.
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