Difference between revisions of "2015 Summer Project Week:T1 mapping"

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Image:T1_Mapping_logo.png|T1 Mapping Logo
 
Image:T1_Mapping_logo.png|T1 Mapping Logo
 
</gallery>
 
</gallery>
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[[File:T1_Mapping_CPP_GUI.png|250px|thumb|left|T1 Mapping C++ GUI]]
 
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[[File:Comparison_T1_Mapping_ALL.png‎|300px|thumb|left|Comparison of Different T1 Mapping Tools]]
 
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[[File:T1_Mapping_Result_Sample.png|250px|thumb|left|Sample Results of T1 Mapping]]
 
  
 
==Key Investigators==
 
==Key Investigators==
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==Project Description==
 
==Project Description==
 
T1 mapping estimates effective tissue parameter maps (T1) from multi-spectral FLASH MRI scans with different flip angles. T1 mapping can be used to optimize parameters for a sequence, monitor diseased tissue, measure Ktrans in DCE-MRI and etc.  
 
T1 mapping estimates effective tissue parameter maps (T1) from multi-spectral FLASH MRI scans with different flip angles. T1 mapping can be used to optimize parameters for a sequence, monitor diseased tissue, measure Ktrans in DCE-MRI and etc.  
 +
[[File:T1_Mapping_CPP_GUI.png|300px|thumb|left|T1 Mapping C++ GUI]]
 +
[[File:Comparison_T1_Mapping_ALL.png‎|400px|thumb|left|Comparison of Different T1 Mapping Tools]]
 +
[[File:T1_Mapping_Result_Sample.png|300px|thumb|left|Sample Results of T1 Mapping]]
 +
 +
== ==
 
<div style="margin: 20px;">
 
<div style="margin: 20px;">
 
<div style="width: 27%; float: left; padding-right: 3%;">
 
<div style="width: 27%; float: left; padding-right: 3%;">
 
<h3>Objective</h3>
 
<h3>Objective</h3>
 
* Estimate effective T1 from multi-spectral FLASH MRI scans with different flip angles
 
* Estimate effective T1 from multi-spectral FLASH MRI scans with different flip angles
−
* Implement T1 mapping algorithm as a Slicer extension using C++  
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* Implement T1 mapping algorithm as a Slicer module using C++  
 
</div>
 
</div>
 
<div style="width: 27%; float: left; padding-right: 3%;">
 
<div style="width: 27%; float: left; padding-right: 3%;">
 
<h3>Approach, Plan</h3>
 
<h3>Approach, Plan</h3>
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* Start with [http://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/Modules/DWModeling prostate diffusion module]
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* Start with [https://www.slicer.org/wiki/Documentation/Nightly/Modules/DWModeling prostate diffusion module]
 
* Update equations for T1 mapping
 
* Update equations for T1 mapping
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* Compare the results using C++, [http://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/Modules/T1_Mapping Python], [https://surfer.nmr.mgh.harvard.edu/fswiki/mri_ms_fitparms  Freesurfer ] with ground truth of T1 for [https://dblab.duhs.duke.edu/modules/QIBAcontent/index.php?id=1  QIBA phantom]
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* Compare the results using C++, [https://www.slicer.org/wiki/Documentation/Nightly/Modules/T1_Mapping Python], [https://surfer.nmr.mgh.harvard.edu/fswiki/mri_ms_fitparms  Freesurfer ] with the ground truth of T1 for [https://dblab.duhs.duke.edu/modules/QIBAcontent/index.php?id=1  QIBA phantom]
 
* Test the Slicer module on MGH Brain Tumor MR Data with multiple flip angles
 
* Test the Slicer module on MGH Brain Tumor MR Data with multiple flip angles
  
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<div style="width: 27%; float: left; padding-right: 3%;">
 
<div style="width: 27%; float: left; padding-right: 3%;">
 
<h3>Progress</h3>
 
<h3>Progress</h3>
−
* Equations have already been updated
+
* Updated the equations for variable flip angle (VFA) T1 mapping
−
* Working on the GUI
+
* Compared the results using C++ with Python, Freesurfer and the ground truth of T1 for QIBA phantom data
−
* Working on the comparison
+
* T1 mapping results on QIBA phantom data using C++ are comparable with the ground truth and the results using Freesurfer and Python
 +
* Did some tests on MGH Brain Tumor MR Data with multiple flip angles
 +
* Created a module for T1 mapping using C++
 +
** Take multi-spectral FLASH images with an arbitrary number of flip angles as input, and estimate the T1 values of the data for each voxel
 +
** Read repetition time(TR), echo time(TE) and flip angles from the Dicom header automatically
 +
** Provide users with options to use ROI mask and choose which flip angles to include or exclude for the fitting process
 +
** Output the fitting volume and quality of fitting image as well
 +
* Uploaded the source code on [https://github.com/stevedaxiao/T1_Mapping_CPP.git Github]
 
</div>
 
</div>
 
</div>
 
</div>
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==References==
 
==References==
  
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* [https://dblab.duhs.duke.edu/modules/QIBAcontent/index.php?id=1 QIBA T1 phantom]
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* [https://sites.duke.edu/dblab/qibacontent/  QIBA T1 phantom]
 
* [http://europepmc.org/articles/pmc3620726 Basic equations for T1 Mapping]
 
* [http://europepmc.org/articles/pmc3620726 Basic equations for T1 Mapping]
 
* [https://github.com/stevedaxiao/T1_Mapping.git Source code for T1 Mapping Python Version]
 
* [https://github.com/stevedaxiao/T1_Mapping.git Source code for T1 Mapping Python Version]
 
* [https://github.com/stevedaxiao/T1_Mapping_CPP.git Source code for T1 Mapping C++ Version]
 
* [https://github.com/stevedaxiao/T1_Mapping_CPP.git Source code for T1 Mapping C++ Version]

Latest revision as of 17:11, 10 July 2017

Home < 2015 Summer Project Week:T1 mapping

Key Investigators

  • Xiao Da (MGH), Yangming Ou (MGH), Andriy Fedorov (BWH), Jayashree Kalpathy-Cramer (MGH)
  • Utsav Pardasani (Observing)

Project Description

T1 mapping estimates effective tissue parameter maps (T1) from multi-spectral FLASH MRI scans with different flip angles. T1 mapping can be used to optimize parameters for a sequence, monitor diseased tissue, measure Ktrans in DCE-MRI and etc.

T1 Mapping C++ GUI
Comparison of Different T1 Mapping Tools
Sample Results of T1 Mapping

Objective

  • Estimate effective T1 from multi-spectral FLASH MRI scans with different flip angles
  • Implement T1 mapping algorithm as a Slicer module using C++

Approach, Plan

Progress

  • Updated the equations for variable flip angle (VFA) T1 mapping
  • Compared the results using C++ with Python, Freesurfer and the ground truth of T1 for QIBA phantom data
  • T1 mapping results on QIBA phantom data using C++ are comparable with the ground truth and the results using Freesurfer and Python
  • Did some tests on MGH Brain Tumor MR Data with multiple flip angles
  • Created a module for T1 mapping using C++
    • Take multi-spectral FLASH images with an arbitrary number of flip angles as input, and estimate the T1 values of the data for each voxel
    • Read repetition time(TR), echo time(TE) and flip angles from the Dicom header automatically
    • Provide users with options to use ROI mask and choose which flip angles to include or exclude for the fitting process
    • Output the fitting volume and quality of fitting image as well
  • Uploaded the source code on Github

References

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