mt_ratio : Magnetization transfer ratio (MTR)ΒΆ


% This m-file has been automatically generated using qMRgenBatch(mt_ratio)
% Command Line Interface (CLI) is well-suited for automatization
% purposes and Octave.
% Please execute this m-file section by section to get familiar with batch
% processing for mt_ratio on CLI.
% Demo files are downloaded into mt_ratio_data folder.
% Written by: Agah Karakuzu, 2017
% =========================================================================


qMRinfo('mt_ratio'); % Describe the model
  mt_ratio :  Magnetization transfer ratio (MTR)

MTR is a semi-quantitative measure. It is not an absolute measure of
magnetization transfer contrast and highly depended on the shape,
bandwidth and frequency offset of the MT pulse.

MTon     MT-weighted data. Spoiled Gradient Echo (or FLASH) with MT
MToff    Data before MT pulse. Spoiled Gradient Echo (or FLASH) without MT
(Mask)    Binary mask.

MTR        Magnetization transfer ratio map (%)

Example of command line usage (see also a href="matlab: showdemo Custom_batch"showdemo Custom_batch/a):
For more examples: a href="matlab: qMRusage(Custom);"qMRusage(Custom)/a

Author: Agah Karakuzu

Please cite the following if you use this module:
In addition to citing the package:
Cabana J-F, Gu Y, Boudreau M, Levesque IR, Atchia Y, Sled JG, Narayanan S, Arnold DL, Pike GB, Cohen-Adad J, Duval T, Vuong M-T and Stikov N. (2016), Quantitative magnetization transfer imaging made easy with qMTLab: Software for data simulation, analysis, and visualization. Concepts Magn. Reson.. doi: 10.1002/cmr.a.21357

Reference page in Doc Center
doc mt_ratio


a- create object

Model = mt_ratio;

b- modify options

         |- This section will pop-up the options GUI. Close window to continue.
|- Octave is not GUI compatible. Modify Model.options directly.
Model = Custom_OptionsGUI(Model); % You need to close GUI to move on.


a- load experimental data

         |- mt_ratio object needs 3 data input(s) to be assigned:
|-   MTon
|-   MToff
|-   Mask
data = struct();

% MTon.mat contains [128  135   75] data.
% MToff.mat contains [128  135   75] data.
% Mask.mat contains [128  135   75] data.
data.MTon= double(MTon);
data.MToff= double(MToff);
data.Mask= double(Mask);

b- fit dataset

           |- This section will fit data.
FitResults = FitData(data,Model,0);

c- show fitting results

         |- Output map will be displayed.
|- If available, a graph will be displayed to show fitting in a voxel.
|- To make documentation generation and our CI tests faster for this model,
we used a subportion of the data (40X40X40) in our testing environment.
|- Therefore, this example will use FitResults that comes with OSF data for display purposes.
|- Users will get the whole dataset (384X336X224) and the script that uses it for demo
via qMRgenBatch(qsm_sb) command.
FitResults_old = load('FitResults/FitResults.mat');

d- Save results

         |-  qMR maps are saved in NIFTI and in a structure FitResults.mat
that can be loaded in qMRLab graphical user interface
|-  Model object stores all the options and protocol.
It can be easily shared with collaborators to fit their
own data or can be used for simulation.
Warning: Directory already exists.


   |- This section can be executed to run simulations for mt_ratio.

a- Single Voxel Curve

         |- Simulates Single Voxel curves:
(1) use equation to generate synthetic MRI data
(2) add rician noise
(3) fit and plot curve
% Not available for the current model.

b- Sensitivity Analysis

         |-    Simulates sensitivity to fitted parameters:
(1) vary fitting parameters from lower (lb) to upper (ub) bound.
(2) run Sim_Single_Voxel_Curve Nofruns times
(3) Compute mean and std across runs
% Not available for the current model.