Hi
My PhD project focuses on developing a realistic thalamocortical model of Alzheimer's disease (AD). One of the major components of my project is to utilize DTI data from AD patients to build the macro-connectivity of the model. Currently, I'm working on FSL + FreeSurfer + CAMINO to process the DTI data.
I'm sending this message to verify my approach in determining the regions of interest and to ask other critical questions.
The approach A) Cortical Segmentation 1- First, I've segmented the T1-weighted image with recon-all command. 2- converted the cortical segmentation image (wmparc.mgz) into the Nifti format using mri_convert.
B) Registration of Segmentation and Diffusion Weighted Image 1- The brain region was extracted from the b0 image using BET command 2- The output of the BET tool was used for the registration with the T1 image using FLIRT tool. 3- Obtain the inverse transformation matrix using convert_xfm in FSL 4- Apply the inverse matrix over the segmentation image with the 'Interpolation Method' as 'Nearest Neighbour' (using FLIRT). 5- Get the labels of Thalamus and cortical areas from usr/local/FreeSurfer/FreeSurferColorLUT.txt. (for cortical areas, I've considered cortical labels that started with 'wm-' but not 'ctx-'. Is that correct?) 6- Apply fslmath to pull out the appropriate ROI(s) 7- Apply Fiber Tracking tool to get fiber data.
Questions: - Can you please advise if I'm doing right in outlining the ROI(s) ? - How can I differentiate between Thalamocortical and corticothalamic fibers ? - How can I get corticocortical fibers ? Is it right to get two cortical labels (source & destination) and find the pathways between them ?
I will highly appreciate any advice/suggestions.
Many Thanks Kamal.