Bayesian construction of geometrically based cortical thickness metrics

This paper describes the construction of cortical metrics quantifying the p robabilistic occurrence of gray matter, white matter, and cerebrospinal flu id compartments in their correlation to the geometry of the neocortex as me asured in 0.5-1.0 mm magnetic resonance imagery. These cortical profiles re present the density of the tissue types as a function of distance to the co rtical surface. These metrics are consistent when generated across multiple brains indicating a fundamental property of the neocortex. Methods are pro posed for incorporating such metrics into automated Bayes segmentation. (C) 2000 Academic Press.