Segmenting magnetic resonance images via hierarchical mixture modelling

Authors:
Carey E. Priebe;Michael I. Miller;J. Tilak Ratnanather
Affiliations:
Center for Imaging Science, Johns Hopkins University, Baltimore, MD 21218, USA;Center for Imaging Science, Johns Hopkins University, Baltimore, MD 21218, USA;Center for Imaging Science, Johns Hopkins University, Baltimore, MD 21218, USA
Venue:
Computational Statistics & Data Analysis
Year:
2006

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Abstract

We present a statistically innovative as well as scientifically and practically relevant method for automatically segmenting magnetic resonance images using hierarchical mixture models. Our method is a general tool for automated cortical analysis which promises to contribute substantially to the science of neuropsychiatry. We demonstrate that our method has advantages over competing approaches on a magnetic resonance brain imagery segmentation task.