On matching brain volumes

摘要

To characterize the complex morphological variations that occur naturally in human neuroanatomy so that their confounding effect can be minimized in the identification of brain structures in medical images, a computational framework has evolved in which individual anatomies are modeled as warped versions of a canonical representation of the anatomy, known as an atlas. To realize this framework, the method of elastic matching was invented for determining the spatial mapping between a three-dimensional image pair in which one image volume is modeled as an elastic continuum that is deformed to match the appearance of the second volume. In this paper, we review the seminal ideas underlying the elastic matching technique, consider the practical implications of an integral formulation of the approach, and explore a more general Bayesian interpretation of the method in order to address issues that are less naturally resolved within a continuum mechanical setting, such as the examination of a solution’s reliability or the incorporation of empirical information that may be available about the spatial mappings into the analysis.