NURBS-based visualization of age-related diversity in cortical morphology

Introduction In neurology, it is known that different motor and cognitive functions in humans are mapped on specific cortical surface patterns of the brain. The variability in these surface patterns between individuals is caused by local differences in the rate of angular deformations of cerebral tissues during brain development. It has been reported that age effects of the human brain result in significant changes in the cortical volume (Courchesne et al., 2000). Moreover, the locations of individual convolutions on the brain surface depend on local changes in cortical structure, with sulci occurring in relation to boundaries between cortical architectonic fields. Additionally, the importance of visualizing medical images, especially in 3D, for clinical applications involving the brain, is immense (Linney and Alusi, 1998). Therefore, a method to analyze and visualize age-related variability of surface patterns is useful in neuro-imaging studies to detect various functional disorders and behavioral changes between children and adults (Kolb, 1993). The investigation in this paper presents a new approach based on statistical analysis of curvature changes in deformation vectors of a NURBS surface to compute and visualize the variability associated with surface patterns of the human brain.