MNE-Python Scale MRI
- 1. Coregistration in mne-python Subjects without MRI
- 2. General Notes • The GUI uses the traits library which supports different backends but seems to work best with QT4 currently. To make QT4 the default: • In Canopy: change Preferences/Python/PyLab backend • In a terminal: $ export ETS_TOOLKIT=“qt4” • The coregistration GUI is a recent addition to MNEPython; please report unexpected behavior to the mne-analysis mailing list
- 3. Overview Select MRI Scale the MRI 3D View Set MRI Fiducials Find Head Shape to MRI Coregistration Select Raw File Control the 3D View Save the Result
- 4. Input Files • Specify the directory containing MRIsubjects (subjects_dir) • Select the Raw file for which to do the coregistration • Select the template brain to use. The default template that comes with freesurfer and MNE is fsaverage. The fsaverage files can be copied into the subjects directory with the “Copy FsAverage to Subject Folder” button (the button does not work if a subject named “fsaverage” already exists). • Fsaverage comes with fiducials which should be automatically loaded, in which case you can skip the next slide.
- 5. Fiducials • Select the fiducial you want to modify, and then click on the head model to specify the position. Fiducials are displayed as small colored spheres. • When all the fiducials are specified, save the positions so they can be loaded in the future. • Lock the fiducials to proceed to the coregistration.
- 6. Coregistration • Use “Fit LPA/RPA” to find an initial approximate alignment
- 7. Coregistration • Head shape and MRI are initially aligned at the nasion. Adjust the nasion alignment to properly align the forehead
- 8. Coregistration • In case the head shape contains outlier points, head shape points can be omitted based on their distance from the MRI head surface (for the sample data, 10 mm is a good distance)
- 9. Scaling • Select the desired number of scaling parameters (scaling with the same factor along all axes or scaling with a separate factor for the X, Y and Z axes) • Use the automatic fitting functions as well as manual adjustment to find a proper MRI scaling factor
- 10. Coregistration • Once a proper scaling factor is found, use the fitting function that don’t scale the MRI as well as manual adjustment to fine tune the coregistration
- 11. Saving • Finally hit the save button to save the scaled MRI as well as the head-MRI transformation in a *-trans.fif file