Welcome to the ASL toolkit!
This library was designed to assist users in processing Arterial Spin Labeling (ASL) MRI images, from basic imaging protocols to the state-of-the-art models provided in the scientific literature.
The major objective of this project is to give an open-source alternative to researchers in the MRI field. A profound knowledge of computing and data modelling is not a prior demand. It is expected that a simple set of Python commands can be helpful in fast prototyping an ASL experiment or even collecting simple quantitative ASL-based information.
Please read the full documentation to get more details about the usage, implementation and updates in the asltk library.
Also, feel free to contribute directly to the project! Check it out the issues at the repository and get in touch to the developers of the project.
A quick to use install is via pip, as follows:
Note
The installation requires Python 3.10 or higher
pip install asltkThe ASLtk library provides a wide range of functionalities for processing Arterial Spin Labeling (ASL) MRI images, including:
- Preprocessing: Tools for denoising, motion correction, and normalization of ASL images.
- Quantification: Methods for calculating perfusion maps and other quantitative metrics from ASL data.
- Visualization: Utilities for visualizing ASL images and results in an intuitive manner.
- Model Implementation: Access to state-of-the-art models for ASL image analysis, allowing users to leverage advanced techniques without deep expertise in the field.
Thank you all the special people that invested their time and knowledge to improve this project. 👏
We appreciate if one or more of the following references can be added in your projects due to the usage of asltk outcomes.
- Senra Filho, A.C.; Paschoal, A. M. "Open-Source Multi-Echo (TE) MRI Tool for Arterial Spin Labelling Imaging Protocols". ISMRM Brazilian Chapter, 2025.