dnnbrain.brain.io module

dnnbrain.brain.io.extract_brain_activation(brainimg, mask, roilabels, method='mean')

Extract brain activation from ROI.

Parameters

• brainimg (array) – A 4D brain image array with the first dimension correspond to pictures and the rest 3D correspond to brain images

• mask (array) – A 3D brain image array with the same size as the rest 3D of brainimg.

• roilabels (list, array) – ROI labels

• method (str) – Method to integrate activation from each ROI, by default is ‘mean’.

Returns

roisignals – Extracted brain activation. Each element in the list is the extracted activation of the roilabels. Due to different label may contain different number of activation voxels, the output activation could not stored as numpy array list.

Return type

list

dnnbrain.brain.io.load_brainimg(imgpath, ismask=False)

Load brain image identified by its suffix. The supporting suffixes are as follows:

Nifti: .nii.gz

freesurfer: .mgz, .mgh

gifti: .func.gii, .shape.gii

cifti: .dscalar.nii, .dlabel.nii, .dtseries.nii

Parameters

imgpath (str) – Brain image data path

Returns

• brain_img (array) – Data of brain image

• header (header) – Header of brain image

dnnbrain.brain.io.save_brainimg(imgpath, data, header)

Save brain image identified by its suffix. The supporting suffixes are as follows:

Nifti: .nii.gz

freesurfer: .mgz, .mgh

cifti: .dscalar.nii, .dlabel.nii, .dtseries.nii

Note that due to ways to store gifti image are differ from other images, we didn’t support to save data as a gifti image.

Parameters

• imgpath (str) – Brain image path to be saved

• data (ndarray) – Brain image data matrix

• header (header) – Brain image header