The brain parcellation methodology is based on a database of 26 normal T1-MR brain scans (all non-smokers; female: 3, left-handed:1, age: 34±12, min 19, max 39). The images were manually segmented by neuroanatomically trained operators as described in Dououd et al. . The parcellation of an individual T1-MR brain scan consists of the following processing steps:
1.Reduction of the noise in the MR image by a non-local means algorithm.
2.Segmentation of the gray matter (GM), white matter (WM) and the cerebrospinal fluid (CSF).
3.Splitting of the left and right hemispheres. This step requires three anatomical points: the anterior commissure (AC), the posterior commissure (PC) and an inter-hemispheric point (IHP). Both hemispheres are processed separately in the following.
4.Definition of a fourth anatomical point located between the caudates, allowing calculation of the average thickness of the frontal horn of the left and right ventricles. The ventricles are known to increase in volume with age and as a consequence of a number of neurological conditions and diseases.
5.Selection of the N most comparable brain hemispheres in the knowledge base using the frontal horn thickness and an inter-caudate point (IC) specified by the user. The optimal number of hemispheres to include is in the order of 8.
6.Each of the selected knowledge base hemispheres is elastically matched to the subject hemisphere using a hierarchical approach. It starts with a global affine transformation and then adjusts each structure separately with a free form deformation algorithm. The result is a set of N structure definitions in the geometry of the subject hemisphere.
7.A maximum probability atlas is derived from the N structure definitions as well as the GM and WM segments, resulting in 16 structures: Structures with separate left/right parts are gray matter, caudate, putamen, thalamus, globus pallidus; structures without laterality are cerebellum and liquor.
8.The gray matter structure is further parcellated into cortical regions by means of an atlas.
1.Douaud G, Gaura V, Ribeiro MJ, Lethimonnier F, Maroy R, Verny C, Krystkowiak P, Damier P, Bachoud-Levi AC, Hantraye P et al: Distribution of grey matter atrophy in Huntington's disease subjects: a combined ROI-based and voxel-based morphometric study. Neuroimage 2006, 32(4):1562-1575. DOI