ORIGINAL ARTICLES: Martijn Froeling (2019), QMRTools: a Mathematica toolbox for quantitative MRI analysis. Journal of Open Source Software, 4(38), 1204, https://doi.org/10.21105/joss.01204​
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Froeling, M., Nederveen, A.J., Heijtel, D.F.R., Lataster, A., Bos, C., Nicolay, K., Maas, M., Drost, M.R. and Strijkers, G.J. (2012), Diffusion-tensor MRI reveals the complex muscle architecture of the human forearm. J. Magn. Reson. Imaging, 36: 237-248. https://doi.org/10.1002/jmri.23608
Overview:
◼
  • Part 1: Why QMRITools`
    • ◼
  • Part 2: Paclet setup and development
    • ◼
  • Part 3: Usage of QMRITools`

    • Part 1: Why QMRITools

    ◼
  • First experience with Mathematica (5.0)
    • ◼
  • Research topic qMRI of muscle and nerve
    • In[]:=
    SystemOpen["D:\\werk\\workspace\\QMRITools\\QMRI.pptx"]
    ◼
  • How did the Paclet start
    • ◼
  • Code for Master and Phd thesis (2008-2012)
    • ◼
  • On Github since 2016 (www.github.com/mfroeling/QMRITools )
    • ◼
  • Published in 2019 (www.doi.org/10.21105/joss.01204 )
    • ◼
  • www.qmritools.com and www.muscle-atlas.org/muscle/lowerlimb
    • PacletInstall["https://github.com/mfroeling/QMRITools/releases/download/3.9.0/QMRITools-3.9.0.paclet"]

    Part 2: Paclet setup and development

    Sep 27 - 2023

    Not all examples shown in this notebook will work since some need data that cannot be shared.
    Those section will be labeled with (*data not available*)
    I did preserve the code for those interested.

    The paclet

    In[]:=
    (*installingthetoolboxanddemodata*)​​(*installfromgit*)​​PacletInstall["https://github.com/mfroeling/QMRITools/releases/download/3.9.0/QMRITools-3.9.0.paclet"]​​(*runtoolboxandextractdemodata*)​​<<QMRITools`​​ExtractDemoData[];
    Out[]=
    PacletObject
    Name: QMRITools
    Version: 3.9.0
    
    QMRITools Documentation

    Content of the paclet

    ◼
  • Functions and toolboxes
    • In[]:=
    Grid[Transpose@{{"SubPackages: ","Exposed Functions: ","Exposed Options: "},​​Length@Flatten[QMRIToolsFunctions[][[All,#]]]&/@{1,2,3}},Alignment->Left]
    Out[]=
    SubPackages:
    25
    Exposed Functions:
    495
    Exposed Options:
    415
    ◼
  • Listing functions
    • In[]:=
    Column@QMRIToolsPackages[]
    In[]:=
    QMRIToolsFunctions["All",3]
    In[]:=
    QMRIToolsFunctions[3]

    Paclet Extensions

    The paclet comes with:
    ◼
  • External executables and libraries that are needed for some functions.
    • ◼
  • Pretrained neural nets
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  • Resources
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  • Demonstration data
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  • Demonstration notebooks
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  • Example extensions
    • In[]:=
    Grid@pac["Extensions"]
    In[]:=
    GetAssetLocation["DemoData"]​​GetAssetLocation["Elastix"]

    Release and development

    Locally can switch between two versions
    ◼
  • <<QMRITools`
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  • The installed paclet of the final public release (PacletInstall)
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  • <<QMRIToolsDev`
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  • Development version (Manually installed in $BaseDirectory\Applications)

    • Git and IDE

    For Git versions control and development:
    ◼
  • Currently working in VSCode + Wolfram Language Extension
    • ◼
  • All files have the same layout
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  • Development in Mathematica *.nb
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  • Once stable move to toolbox *.wl using VSCode not Mathematica
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  • Write documentation / specify options and error messages

    • Contexts and Loader

    ◼
  • QMRITools` Loads all other sub-packages and adds them to the ContextsPath.
    • ◼
  • Listing context
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  • Toolboxes are aware of each other
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  • Visualizing Toolboxes function dependencies
    • ◼
  • Main processing function: MuscleBidsProcess

    • Building and deployment

    ◼
  • Build scripts
    • www.qmritools.com/assets/htmldoc/html/guide/qmritools

    Working with numeric data

    ◼
  • Typical 45 min scan protocol generates ~9000 dicom “Images” or rather 18 dicom datasets.
    • ◼
  • Balance memory dependency, speed, usability
    • ◼
  • $HistoryLength = 0
    • ◼
  • Example Data
    • ◼
  • Keep most data Packed and Numeric (ToPackedArray@N@...)

    • Functions that are used a lot

    ◼
  • Block and Manipulate
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  • Compile
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  • Handling non numeric data and zero
    • ◼
  • SpacreArray; Pick; Unitize; UnitStep;
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  • Favorite custom functions
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  • ImportNii
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  • RotateDimensions
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  • Masking
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  • Cropping
    • ◼
  • PlotData (PlotData 3D)

    • Part 3: Usage of QMRITools`

    Demonstration of Toolbox functionality

    Data Visualization

    ◼
  • Slice images
    • ◼
  • 3D segmentations

    • Water Fat Imaging

    ◼
  • MR data is complex valued
    • ◼
  • Phase Unwrapping
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  • Simulate some data
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  • Best path phase unwrapping
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  • Discrete cosine unwrap
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  • Real data
    • ◼
  • Dixon reconstruction using iDEAL
    • ◼
  • Segment data with CNN

    • Extended phase graph T2 mapping

    ◼
  • Simulation of RF slice profiles
    • ◼
  • Bloch equations
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  • RF and slice profile
    • ◼
  • EPG Fitting
    • ◼
  • Fitting using dictionary lookup
    • ◼
  • Making dictionary
    • ◼
  • Caching results

    • Diffusion Tensor Imaging

    ◼
  • Import demo data
    • ◼
  • Designing the experiment
    • ◼
  • Processing the data: Denoising
    • ◼
  • Data preparation
    • ◼
  • Remove noise from data
    • ◼
  • Motion Correction

    • Diffusion Tensor Imaging tractography

    ◼
  • Importing fully processed data
    • ◼
  • Muscle fibre tractography

    • Diffusion Tensor Imaging tractography

    The following section wont work since the data is not available
    ◼
  • Import Data
    • ◼
  • Evaluate tracts
    • ◼
  • Making contours
    • ◼
  • Making tracts
    • ◼
  • Making Full scene

    • CITE THIS NOTEBOOK

    Wolfram R&D LIVE: QMRITools - Processing Quantitative MRI Data​
    by Martijn Froeling​
    Wolfram Community, STAFF PICKS, October 2, 2023
    ​https://community.wolfram.com/groups/-/m/t/3025910