SRQL 2.0: Automated White Matter Segmentation

SRQL v2.0 no longer requires user input of a healthy white matter mask, but instead automatically performs a white matter segmentation (using FSL FAST) for white matter intensity correction. This version also comes with a new quality control feature, which allows users to visualize the final output of the white-matter corrected lesion mask (requires FSLeyes). SRQL v2.0 no longer supports standardization to stereotaxic space.

Semi-automated Robust Quantification of Lesions (SRQL) Toolbox version 1.1

Semi-automated Robust Quantification of Lesions (SRQL; https://github.com/npnl/SRQL) Toolbox. The toolbox performs the following analysis steps: 1) a white matter intensity correction that removes healthy white matter voxels from the lesion mask, thereby making lesions slightly more robust to subjective errors; 2) an automated report of descriptive statistics on lesions for simplified comparison between or across groups, and 3) an option to perform analyses in both native and standard space to facilitate analyses in either space, or comparisons between spaces.

Updated 20170424: This build has a few bug fixes to facilitate use on remote linux servers.

Semi-automated Robust Quantification of Lesions (SRQL) Toolbox version 1.0

First release of the Semi-automated Robust Quantification of Lesions (SRQL; https://github.com/npnl/SRQL) Toolbox. The toolbox performs the following analysis steps: 1) a white matter intensity correction that removes healthy white matter voxels from the lesion mask, thereby making lesions slightly more robust to subjective errors; 2) an automated report of descriptive statistics on lesions for simplified comparison between or across groups, and 3) an option to perform analyses in both native and standard space to facilitate analyses in either space, or comparisons between spaces.