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Graphical shape templates for automatic anatomy detection with applications to MRI brain scans

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1 Author(s)
Y. Amit ; Dept. of Stat., Chicago Univ., IL, USA

A new method of model registration is proposed using graphical templates. A decomposable graph of landmarks is chosen in the template image. All possible candidates for these landmarks are found in the data image using robust relational local operators. A dynamic programming algorithm on the template graph finds the optimal match to a subset of the candidate points in polynomial time. This combination-local operators to describe points of interest/landmarks and a graph to describe their geometric arrangement in the plane-yields fast and precise matches of the model to the data with no initialization required. In addition, it provides a generic tool box for modeling shape in a variety of applications. This methodology is applied in the context of T2-weighted magnetic resonance (MR) axial and sagittal images of the brain to identify specific anatomies.

Published in:

IEEE Transactions on Medical Imaging  (Volume:16 ,  Issue: 1 )