ASLPrep: A Robust Preprocessing Pipeline for ASL Data¶
This pipeline is developed by the Satterthwaite lab at the University of Pennysilvania for use at the The Lifespan Informatics and Neuroimaging Center at the University of Pennylvannia, as well as for open-source software distribution.
ASLPrep is a Arterial Spin Labeling (ASL) data preprocessing and Cerebral Blood FLow (CBF) computation pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to variations in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting. It performs basic processing steps (coregistration, normalization, unwarping, noise component extraction, segmentation, skullstripping etc.), CBF computation, denoising CBF, CBF partial volume correction and providing outputs that can be easily submitted to a variety of group level analyses, including task-based or resting-state CBF, graph theory measures, surface or volume-based statistics, etc.
The ASLPrep pipeline uses a combination of tools from well-known software packages, including FSL, ANTs, FreeSurfer and AFNI . This pipeline was designed to provide the best software implementation for each state of preprocessing, and will be updated as newer and better neuroimaging software become available.
This tool allows you to easily do the following:
- Take ASL data from raw to fully preprocessed form.
- Compute Cerebral Blood Flow(CBF), denoising and partial volume correction
- Implement tools from different software packages.
- Achieve optimal data processing quality by using the best tools available.
- Receive verbose output concerning the stage of preprocessing for each subject, including meaningful errors.
- Automate and parallelize processing steps, which provides a significant speed-up from typical linear, manual processing.
More information and documentation can be found at https://aslprep.readthedocs.io/
ASLPrep adapts the preprocessing steps depending on the input dataset and provide results as good as possible independently of scanner make and scanning parameters With the BIDS input, little or no parameter are required allowing ease of operation. ASLPrep also provides visual reports for each subject, detailing the the most important processing steps.
Please acknowledge this work using the citation boilerplate that ASLPrep includes in the visual report generated for every subject processed. (link)
We use the 3-clause BSD license; the full license may be found in the LICENSE file in the ASLPrep distribution.
All trademarks referenced herein are property of their respective holders.
Copyright (c) 2019-2020, Azeez Adebimpe All rights reserved.
- ASLPrep Installation
- Usage Notes
- Execution and the BIDS format
- Command-Line Arguments
- Positional Arguments
- Named Arguments
- Options for filtering BIDS queries
- Options to handle performance
- Workflow configuration
- Specific options for ANTs registrations
- Specific options for handling fieldmaps
- Specific options for SyN distortion correction
- Specific options for FreeSurfer preprocessing
- Other options
- The FreeSurfer license
- Running ASLPrep via Docker containers
- Running ASLPrep via Singularity containers
- Quick Start Tutorial
- ASL processing pipeline details
- Structural Preprocessing
- ASL preprocessing
- CBF Computation in native space
- Quality control measures
- ASL and CBF to T1w registration
- Susceptibility Distortion Correction (SDC)
- Outputs of ASLPrep
- Standard and nonstandard spaces
- Contributing to ASLPREP
- Developers - API
- What’s new