Software

Anonymize-dicom is a simple GUI tool used for de-identifying information in the dicom headers.

GitHub

DDSeg is a deep learning tissue segmentation method to segment WM, GM and CSF directly using diffusion MRI data. The code allows tissue segmentation using DTI parameters (single shell dMRI data) and DKI parameters computed using MKCurve (multi shell dMRI data with MKCurve corrected data).

GitHub

Eddy-squeeze is a python toolbox used to visualize how FSL Eddy’s outlier replacement function changes the outlier slices. It also extracts information from an Eddy session, such as number of shells detected in the data, number of outlier slices and standard deviation of each outlier slice, and motion etc. into a user-friendly html file.

GitHub

ME-GCM is a Matlab toolbox to compute minimum-entropy based Granger causality measures for brain network analysis using functional MRI. It uses state-space representations to compute the frequency-domain causality measures.

GitHub

Tracing white matter fiber bundles through crossing-fiber regions requires consistent estimation of the fiber orientation as well as microstructural measures (e.g. FA, MD, kurtosis, axon diameter, etc.). The UKF-based method performs simultaneous fiber model estimation and tractography by accounting for the correlation in diffusion along the fiber bundles. This ensures proper estimation of the model parameters (e.g. eigenvalues, eigenvectors, free-water fraction etc.) along the fiber bundles. Currently, the tractography method supports single tensor, 2-tensor, 2-tensor with free-water (recommended), and NODDI fiber models. It also supports an arbitrary number of gradient directions and b-values, although more data always ensures better model fitting and tractography. The algorithm can be used using standalone scripts as well as part of the 3D Slicer platform. It was also one of the winners of the Fiber Cup Tractography Challenge held as part of the MICCAI international conference.

GitHub

Integrated study of multi-site diffusion MRI (dMRI) data can enable diagnosis, monitoring, and treatment of several brain diseases. However, data acquired on a variety of scanners cannot be integrated due to differences in acquisition parameters and scanner artifacts. Therefore, dMRI data has to be harmonized for joint analysis by removing scanner-specific differences.

dMRIharmonization is a Python command line module that implements a method capable of removing scanner-specific effects. The proposed method eliminates inter-site variability in acquisition parameters, while preserving inter-subject anatomical variability.

GitHub

Nifti-snapshot is a python toolbox to quickly create png or jpeg screenshots of 3D nifti files.

GitHub

PICASO is a Matlab toolbox for precise inference and characterization of structural organization (PICASO) of tissue from molecular diffusion. It uses multi-shell diffusion MRI data to estimate the diffusivity and the microstructural disturbance function.

GitHub

PNL-Randomise is a python toolbox for running FSL Randomise on the TBSS output. It splits and parallelizes the randomise using the Bsub job system. It also creates a summary of Randomise outputs in a html file, so the user can easily check and share the result.

GitHub

Quick-QC is a python toolbox for checking for deviations in a newly scanned MRI data compared to a previous scan for a long term cohort studies. Information from the dicom and nifti headers are compared to that of the previous scan and the unexpected deviations are reported. In addition to the comparison, it also runs multi-modal preprocessing tools to extract measures that represent quality of the data included in the scan.

GitHub

REDIM is a Matlab toolbox for modeling and analyzing diffusion MRI data with multiple echo times, i.e., joint relaxation-diffusion imaging. It provides the joint moments of the T2 relaxation rates and the diffusivity and can apply filters to emphasize signals with fast or slow diffusion/relaxation coefficients.

GitHub

The MK-Curve method aims at detecting and correcting voxels with implausible values to enable improved diffusion kurtosis imaging (DKI) parameter estimation.

GitHub

This software implements a non-parametric representation termed Spherical Ridgelets to sparsely represent dMRI data on the sphere. It also allows to reduce the number of gradient directions required to represent the signal thereby reducing the scan time significantly. It also estimates the orientation distribution function (ODF) and the number of fibers at each voxel. This method was the winner of the SPARC dMRI Challenge.

GitHub

This project is an open source framework for the development and execution of magnetic resonance (MR) pulse sequences for imaging and spectroscopy.The MRI sequences can be programmed directly in MATLAB and executed on MR scanners from any vendor (currently supported, Siemens, GE. In-development: Philips). Harmonized sequence development and reconstruction will minimize inter-scanner differences which contributes to the significant amount of variability in the data acquired across sites. Further, our framework significantly improves reproducibility and reliability of neuroimaging studies.

GitHub

3D Slicer is a free, open source and multi-platform software package widely used for medical, biomedical and related imaging research. It was developed by the Surgical Planning Laboratory with contributions, support and feedback from the PNL.

GitHub