Documentation/Nightly/Extensions/Slicer ASLtoolkit

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Introduction and Acknowledgements

This work was funded by State University of Campinas, Sao Paulo, Brazil.
Author: Antonio Carlos da S. Senra Filho, LOAM Laboratory (State University of Campinas, Department of Cosmic Rays and Chronology)
Contact: Antonio Carlos da S. Senra Filho senraf@unicamp.br

LOAM Laboratory  
State University of Campinas  


Extension Description

ASLtoolkit-logo.png

The ASL toolkit is a library that was designed to assist users to process Arterial Spin Labeling (ASL) MRI images, since basic imaging protocols until the state-of-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. However, a profound knowledge of computing and data modeling is not a prior demand. It is expected that a simple set of python commands can be helpful to fast prototyping an ASL experiment or even collect simple quantitative ASL-based information.

This module was created in 3D Slicer to be another alternative to use the asltk framework, using a simple and quick-to-use graphical interface. The general usage here is basically the same pattern as using the python tool provided at `asltk` library. Further details can be found at the asltk official documentation.

All the project is maintained as an open-source initiative and further assistance in coding maintance and new features can be create by a community of developers. To follow the updates or even help the project, please visit the official asltk website.



Modules

Use Cases

Most frequently used for these scenarios:

  • Use Case 1:
    • Create the basic CBF and ATT maps using the pCASL ASL MRI imaging protocol
  • Use Case 2:
    • Create the T1 relaxation time exchange between blood and csf, as presented at Leonie Petitclerc, et al. (2021).

References

  • Leonie Petitclerc, et al. "Ultra-long-TE arterial spin labeling reveals rapid and brain-wide blood-to-CSF water transport in humans", Neuroimage (2021). DOI: 10.1016/j.neuroimage.2021.118755


Information for Developers


Repositories: