Utilities for Data Processing

We share a series of matlab scripts that may help the researchers to process the data generated by BrainSuite and SVReg sequence.

WARNING: These scripts have not been thoroughly tested and are made available as is. Please use it at your own risk.

Please feel free to send us your feedback to me Anand Joshi: email: ajoshi@sipi.usc.edu

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Contents:

1. Smoothing functions on surfaces (main_smooth_func.m)

2. Group Differences - ROIwise and pointwise (main_grp_diff_ptwise.m, main_grp_diff_roiwise.m) 3. Inverting the volumetric map (main_inv_map.m) 4. Regenerating stats file after manual corrections to the label file (main_manual_roi_corr.m) 5. Labeling of surfaces and volumes based on manually drawn cortical ROIs (main_sulci_surf_corr.m) 1. Smoothing Functions on the surfacesThis function allows us to smooth surface valued data with respect to the geometry of the surface. There are two types of smoothing parameters, laplacian regularization and gradient regularization. The function can also perform anisotropic smoothing with respect to the cortex.function fs=smooth_surf_function(s,f,sl,sg,[anisotropy],[normalize])s: patch surface structure as is typically generated by readdfs functionf: a function specified on the surface as specified by Nx1 arraysl: is an Laplacian based regularizationsq: gradient based regularizationfs: smoothed functionanisotropy [optional]: Nx1 anisotropy terms if we want anisotropic smoothingnormalize: 1 if we want the smoothed function to integrate to the same as original unsmoothed functionf=smooth_surf_function(s,s.attributes,3.1,3.1); example: An example function is provided in main_smooth_func.m 2. Group Differences2a. ROIwise group differences:group_differences.mWe provide a sample script that performs a ROIwise group differences. We assume that the brainsuite and svreg sequences have been run on all the subjects in the two groups. Each subject is in its own subdirectory and inside its group directory. 2b. Vertexwise group differencesgroup_differences_vertexwise.mWe provide a sample script that performs a group differences, per vertex, of cortical feature such as curvature, thickness, etc. We assume that the brainsuite and svreg sequences have been run on all the subjects in the two groups. Each subject is in its own subdirectory and inside its group directory. Currently the script is set up for thickness differences. 3. Invert volumetric map from subject to atlasBy defaults, svreg computes a map from subject to atlas. Oftentimes, we need a map from atlas to subject. This can be done by using invert map computation. Here is a function for this task.inv_subject_map (subbasename, atlasbasename) example usage is shown in main_inv_map.mThe filenames and paths in this function need to be adjusted to work for your configuration.

4. Regenerate stats file after manual corrections are done on the volume labels.Manual corrections can be made to svreg generated labels <subbasename. .svreg.corr.label.nii.gz> with the label painter tool on the BrainSuite GUI interface. http://brainsuite.bmap.ucla.edu/delineation/roi/label-painter-tool/ It assumes that the corrected volumetric labels are stored in [subbasename,'.svreg.corr.manual.label.nii.gz']. Surfaces can be relabeled according to edited labels for the labels which are edited, and then volumetric and suface based statistics can be recomputed using the following function: manual_correct_rois_stats(subbasename)A sample example of usage is shown in main_manual_roi_corr.m 5. Labeling of surfaces and volumes based on manually drawn cortical ROIsROI’s can be manually edited on the midcortical surface generated by SVReg by drawing a sulci that encircles the entire ROI visible on the midcortical surface. $file:///C:\Users\ajoshi\AppData\Local\Temp\OICE_06ECC7FF-034E-4967-A0FE-3B2121C12E90.0\msohtmlclip1\01\clip_image002.gif$ The start and stop point of the sulci should be as close as possible and saved as <subbasename. %%% .dfc> where %%% is the 3 digit ID that is assigned to a particular ROI found in the xml file: brainsuite_labeldescription.xml (located in the atlas folder or your SVReg output folder) or the label painter tool in the BrainSuite GUI interface. If the sulci does not fully enclose the whole ROI, the tool will enclose the sulci by finding the shortest path. $file:///C:\Users\ajoshi\AppData\Local\Temp\OICE_06ECC7FF-034E-4967-A0FE-3B2121C12E90.0\msohtmlclip1\01\clip_image004.gif$ Vertices enclosed by the sulci are relabeled according to the ROI ID number designated and unlabeled vertices are relabeled by nearest neighbor. After which the labels are transferred to inner and pial surfaces. $file:///C:\Users\ajoshi\AppData\Local\Temp\OICE_06ECC7FF-034E-4967-A0FE-3B2121C12E90.0\msohtmlclip1\01\clip_image006.gif$ Surfaces are saved with the extension <.cortex.svreg.surf_corr.dfs> $file:///C:\Users\ajoshi\AppData\Local\Temp\OICE_06ECC7FF-034E-4967-A0FE-3B2121C12E90.0\msohtmlclip1\01\clip_image008.gif$ $file:///C:\Users\ajoshi\AppData\Local\Temp\OICE_06ECC7FF-034E-4967-A0FE-3B2121C12E90.0\msohtmlclip1\01\clip_image010.gif$ Volume labels are then relabeled according to corrections made on the surface and saved as <subbasename.svreg.corr.surf_corr.label.nii.gz>. Multiple ROI’s can be corrected on each run but each sulci must be saved separately with corresponding ROI ID’s . Sulci must be placed in the SVReg output folder that is used as your input directory.A sample is shown in main_sulci_surf_corr.m 5. Invert volumetric map from subject to atlasBy default, SVReg computes a map from subject to atlas. Sometimes, in some applications, one might need a map from atlas to surface which is the inverse map. This can be computed by using the function inv_subject_map.mA sample is shown in main_inv_map.m