Quantification of age-related brain cortex change using 3D shape analysis

To characterize the brain changes associated with aging, we detect brain cortex variability through a spherical harmonic analysis that represents a 3D surface supported by the unit sphere through a linear combination of special basis functions, called spherical harmonics (SHs). The proposed 3D shape analysis is carried out in four steps: (i) 3D Delau-nay triangulation to construct a 3D mesh model of the brain cortex surface; (ii) mapping this model to the unit sphere; (iii) computing the SHs for the surface; and (iv) calculating the area under the error reconstruction curve for the SHs to delineate the brain cortex. We describe the brain shape complexity with a new shape index, the estimated area under the error reconstruction curve for the SHs. The initial experiments on 187 male subjects (age range, 4-22 years) and the comparison results with the cortex volumetric index suggest that our shape index is a promising supplement to current metrics that characterize age-related brain changes.