Difference between revisions of "Documentation/Nightly/Extensions/Slicer ASLtoolkit"

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This work was funded by State University of Campinas, Sao Paulo, Brazil.<br>
 
This work was funded by State University of Campinas, Sao Paulo, Brazil.<br>
 
Author: Antonio Carlos da S. Senra Filho, LOAM Laboratory (State University of Campinas, Department of Cosmic Rays and Chronology)<br>
 
Author: Antonio Carlos da S. Senra Filho, LOAM Laboratory (State University of Campinas, Department of Cosmic Rays and Chronology)<br>
Contact: Antonio Carlos da S. Senra Filho <email>senraf@unicamp.br</email><br>
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Contact: Antonio Carlos da S. Senra Filho senraf@unicamp.br
 
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|Image:LOAM-logo.png|LOAM Laboratory  
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|Image:LOAMRI-logo.png|LOAM Laboratory  
 
|Image:Unicamp-logo.png|State University of Campinas
 
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[[Image:ASLtoolkit-logo.png|left]]
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[[Image:ASLtoolkit-logo.png|left|300px]]
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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.
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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.
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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.
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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.
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ASL toolkit is ... <ref>Authors (2015). Paper. DOI: </ref>.
 
  
  
 
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{{documentation/{{documentation/version}}/extension-section|Modules}}
 
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* '''Structural image denoising with tissues border preservation function''': [[Documentation/{{documentation/version}}/Modules/AADImageFilter|AAD Image Filter]]
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* '''CBF ATT Mapping''': [[Documentation/{{documentation/version}}/Modules/CBFATTMapping|CBF ATT Mapping]]
* '''Structural image denoising without tissues border preservation function''': [[Documentation/{{documentation/version}}/Modules/IADImageFilter|IAD Image Filter]]
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* '''MultiTE ASL Mapping''': [[Documentation/{{documentation/version}}/Modules/MultiTEASLMapping|MultiTE ASL Mapping]]
* '''Diffusion-weighted MR image denoising with tissues border preservation''': [[Documentation/{{documentation/version}}/Modules/AADDiffusionWeightedData|AAD on DWI Image]]
 
* '''Echo-planar imaging denoising with tissues border preservation (fMRI and ASL)''': [[Documentation/{{documentation/version}}/Modules/AADEPIData|AAD on EPI Image]]
 
  
 
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Most frequently used for these scenarios:
 
Most frequently used for these scenarios:
 
* Use Case 1:  
 
* Use Case 1:  
** Another explanation
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** Create the basic CBF and ATT maps using the pCASL ASL MRI imaging protocol
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* Use Case 2:
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** Create the T1 relaxation time exchange between blood and csf, as presented at Leonie Petitclerc, et al. (2021).
  
 
<gallery widths="400px" heights="400px" perrow="3">
 
<gallery widths="400px" heights="400px" perrow="3">
Image:MRI_raw.png|Raw T1 weighted MRI Image
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Image:CBFMap.png|CBF map
Image:MRI_AAD.png|T1 weighted MRI Image with AAD filter (q=1.2)
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Image:ATTMap.png|ATT map
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Image:T1BlGM-multiTE.png|MultiTE-ASL T1 blood-GM map
 
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{{documentation/{{documentation/version}}/extension-section|Similar Extensions}}
 
*[[Documentation/{{documentation/version}}/Modules/GradientAnisotropicDiffusion|Gradient Anisotropic Diffusion]]
 
  
 
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{{documentation/{{documentation/version}}/extension-section|References}}
 
{{documentation/{{documentation/version}}/extension-section|References}}
* da S Senra Filho, A.C., Garrido Salmon, C.E. & Murta Junior, L.O., 2015. Anomalous diffusion process applied to magnetic resonance image enhancement. Physics in Medicine and Biology, 60(6), pp.2355–2373. DOI: 10.1088/0031-9155/60/6/2355
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* 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
  
  
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Repositories:
 
Repositories:
* Source code: [https://github.com/CSIM-Toolkits/AnomalousFiltersExtension GitHub repository]
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* Issue tracker:  [https://github.com/CSIM-Toolkits/AnomalousFiltersExtension/issues open issues and enhancement requests]
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*Source code: [https://github.com/LOAMRI/Slicer-ASLtoolkit GitHub repository]
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*Issue tracker:  [https://github.com/LOAMRI/Slicer-ASLtoolkit/issues open issues and enhancement requests]
  
 
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<references />

Latest revision as of 15:03, 4 October 2024

Home < Documentation < Nightly < Extensions < Slicer ASLtoolkit


For the latest Slicer documentation, visit the read-the-docs.


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: