A major focus of computational anatomy is to extract the most relevant information to identify and characterize
anatomical variability within a group of subjects as well as between different groups. The construction of atlases
is central to this effort. An atlas is a deterministic or probabilistic model with intensity variance, structural,
functional or biochemical information over a population. To date most algorithms to construct atlases have
been based on a single subject assuming that the population is best described by a single atlas. However, we
believe that in a population with a wide range of subjects multiple atlases may be more representative since
they reveal the anatomical differences and similarities within the group. In this work, we propose to use the
K-means clustering algorithm to partition a set of images into several subclasses, based on a joint distance which
is composed of a distance quantifying the deformation between images and a dissimilarity measured from the registration residual. During clustering, the spatial transformations are averaged rather than images to form cluster centers, to ensure a crisp reference. At the end of this algorithm, the updated centers of the k clusters
are our atlases. We demonstrate this algorithm on a subset of a public available database with whole brain
volumes of subjects aged 18-96 years. The atlases constructed by this method capture the significant structural
differences across the group.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.