ExploreASL is a pipeline and toolbox for image processing and statistics of arterial spin labeling perfusion MR images. It is designed as a multi-OS, open source, collaborative framework that facilitates cross-pollination between image processing method developers and clinical investigators.

The software provides a complete head-to-tail approach that runs fully automatically, encompassing all necessary tasks from data import and structural segmentation, registration and normalization, up to CBF quantification. In addition, the software package includes and quality control (QC) procedures and region-of-interest (ROI) as well as voxel-wise analysis on the extracted data. To-date, ExploreASL has been used for processing ~10000 ASL datasets from all major MRI vendors and ASL sequences, and a variety of patient populations, representing ~30 studies. The ultimate goal of Explore ASL is to combine data from multiple studies to identify disease related perfusion patterns that may prove crucial in using ASL as a diagnostic took and enhance our understanding of the interplay of perfusion and structural changes in neurodegenerative pathophysiology.


Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners. The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. The toolbox adheres to previously defined international standards for data structure, provenance, and best analysis practice. ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow. ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts to increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.
Henk Mutsaerts
Image Type
Arterial spin labelling

Additional Information

DOI Citation
Operating System
none, libraries (e.g. SPM) are included
Academic Use
Commercial Use
At Cost
Development Status
Ongoing Support
Source Type
Open Source
Validation Status
2+ Independent Sample
Fully automated
Intended Population
Larger samples
BIDS Compatibility