The long-term goal of our work is to develop improved methods' to objectively perform quantItative analysis of images that are considered to reflect cerebral anatomy (magnetic resonance imaging or x-ray computed tomography) and to define standard anatomic regions of interest that may be used to extract data from images that represent brain function, like positron emission tomography or single photon emission computed tomography. We have implemented a system that elastically deforms a three-dimensional anatomic atlas to match structural images of the human brain. The result is an """"""""individualized"""""""" atlas of the patient's brain which can be used to perform a variety of analyses. This proposal, based on our preliminary evaluation of the current matching system, aims to investigate and implement the following improvements to make the system powerful enough and practical for clinical application: incorporate additional features as a basis for matching including landmarks defined within the brain and on its cortical surface; employ the finite element method and investigate different deformation models to improve the efficiency and accuracy of the solutions; investigate the systematic specification of values for model parameters which control the amount of morphological variation the system should account for; develop a more general, Bayesian approach to the matching problem to accommodate arbitrary noise and distortion models; and to augment our current anatomic atlas of the human brain to include outlines for a comprehensive set of cortical structures. The system will be evaluated by comparison with experts and with the use of real and simulated data.
