Labeling Brain Structures
All code for this document is located at here.
In Processing Within-Visit MRI we show how to register a T1-weighted image to the Eve template. The Eve template has two full brain segmentations and one white matter segmentations, each done by hand. I will refer to these as “atlases” because they tell you “where” you are in the brain with the corresponding labels.
1 Labels in template space
In Processing Within-Visit MRI, we registered the T1 image to the Eve template using a non-linear registration (SyN) (Avants et al. 2008). Also, we applied this transformation to the intensity-normalized T1, T2, and FLAIR images, so that these image are located in the same space as the Eve atlases. We can overlay the atlases on these registered images and look at the average intensity of each structure for each imaging sequence.
1.1 Reading in registered images
Here we will be reading in those previous registered, intensity-normalized images.
library(neurobase) mods = c("T1", "T2", "FLAIR") norm_reg_files = file.path("..", "preprocess_mri_within", paste0("113-01-", mods, "_norm_eve.nii.gz") ) names(norm_reg_files) = mods norm_reg_imgs = lapply(norm_reg_files, readnii)
1.2 Reading in Eve brain
Here we will read in the brain-extracted Eve T1 image, the brain mask, and then mask the normalized images with this mask.
library(EveTemplate) eve_brain_fname = getEvePath("Brain") eve_brain = readnii(eve_brain_fname) eve_brain_mask = readEve(what = "Brain_Mask") norm_reg_imgs = lapply(norm_reg_imgs, mask_img, mask = eve_brain_mask)
We will plot the registered subject images against this to ensure they are in fact in the same space. (Remember to always look at your data!)
lapply(norm_reg_imgs, double_ortho, x = eve_brain)