Difference between revisions of "Documentation/Nightly/Modules/T1Mapping"

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This work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, and by National Cancer Institute as part of the Quantitative Imaging Network initiative (U01CA154601) and QIICR (U24CA180918).<br>
 
This work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, and by National Cancer Institute as part of the Quantitative Imaging Network initiative (U01CA154601) and QIICR (U24CA180918).<br>
  
Implementation of the T1 Mapping was contributed by Xiao Da from MGH. This is a C++ version.<br>
+
Implementation of the T1 Mapping was contributed by Xiao Da from MGH. <br>
  
 
Author: Xiao Da (MGH), Yangming Ou (MGH), Andriy Fedorov (BWH) and Jayashree Kalpathy-Cramer (MGH)<br>
 
Author: Xiao Da (MGH), Yangming Ou (MGH), Andriy Fedorov (BWH) and Jayashree Kalpathy-Cramer (MGH)<br>

Revision as of 03:47, 11 September 2015

Home < Documentation < Nightly < Modules < T1Mapping


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Introduction and Acknowledgements

T1 Mapping Logo Resized CPP.png

Extension: T1Mapping

Acknowledgments: This work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, and by National Cancer Institute as part of the Quantitative Imaging Network initiative (U01CA154601) and QIICR (U24CA180918).

Implementation of the T1 Mapping was contributed by Xiao Da from MGH.

Author: Xiao Da (MGH), Yangming Ou (MGH), Andriy Fedorov (BWH) and Jayashree Kalpathy-Cramer (MGH)
Contact: Xiao Da, <email>XDA@mgh.harvard.edu</email>

National Alliance for Medical Image Computing (NA-MIC)  
Quantitative Image Informatics for Cancer Research  
Martinos Center for Biomedical Imaging  


Module 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.

The method and equations for Variable Flip Angle T1 Mapping are available here: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3620726/pdf/nihms-423474.pdf

Use Cases

  • 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 directly.
  • Prostate, brain, head & neck, cervix, breast and etc.
Sample Results of T1 Mapping
Comparison of Different T1 Mapping Tools

Tutorials

Panels and their use

T1 Mapping C++ GUI
  • Input
    • Input image: Multivolume node containing multiple flip angles image loaded using DICOM module
    • Model: VFA, Variable Flip Angle
    • Input mask: Segmentation of the region of interest (optional); if specified, model fitting will be performed only within the specified mask
    • Flip Angles to include: List of Flip Angles that should be used in the fitting process (optional); this parameter is used only if not empty
    • Flip Angles to exclude: List of Flip Angles that should NOT be used in the fitting process (optional); this parameter is used only if not empty
  • Output common to all models
    • Fitted volume: Multi-volume containing the fitted model sampled at the Flip Angles of the input dataset (optional)
    • Quality of fit volume: R-squared (optional)
  • VFA model output
    • T1 Map: T1 mapping result calculated at each voxel

Similar Modules


References

Information for Developers


Source code: https://github.com/stevedaxiao/T1_Mapping_CPP