denoising_mppca_notebook.ipynb

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"# I- DESCRIPTION"
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"qMRinfo('denoising_mppca'); % Describe the model"
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"# II- MODEL PARAMETERS\n",
"## a- Create object"
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"Model = denoising_mppca;"
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"## Download sample data from OSF\n",
"> The current `Model` is an instance of `denoising_mppca` class.\n",
" \n",
"You can manually download the sample data for `denoising_mppca` [by clicking here](https:\/\/osf.io\/j5239\/download?version=2)."
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"dataDir = downloadData(Model,pwd);"
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"## b- Set protocol\n",
"> Protocol is set according to the example data\n",
" \n",
"%          |- denoising_mppca object needs 0 protocol field(s) to be assigned:"
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"# III- FIT EXPERIMENTAL DATASET\n",
"## a- Load experimental data\n",
"%          |- denoising_mppca object needs 2 data input(s) to be assigned:\n",
"%          |-   Data4D\n",
"%          |-   Mask"
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"% Data4D.nii.gz contains [70   70    4  197] data.\n",
"data.Data4D=double(load_nii_data('denoising_mppca_data\/Data4D.nii.gz'));\n",
" "
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"## b- Fit experimental data\n",
"> This section will fit data."
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"FitResults = FitData(data,Model,0);"
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"## c- Show fitting results\n",
"> * Output map will be displayed.\n",
" \n",
"> * If available, a graph will be displayed to show fitting in a voxel."
]
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"qMRshowOutput(FitResults,data,Model);"
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"## d- Save results\n",
"> * qMR maps are saved in NIFTI and in a structure `FitResults.mat` that can be loaded in qMRLab graphical user interface.\n",
"> * Model object stores all the options and protocol\n",
"> * These objects can be easily shared or be used for simulation."
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"FitResultsSave_nii(FitResults, 'denoising_mppca_data\/Data4D.nii.gz');"
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