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Graphical Shape Templates for Automatic Anatomy Detection with Applications to MRI Brain Scans
 

Summary: 1
Graphical Shape Templates for Automatic Anatomy
Detection with Applications to MRI Brain Scans
Yali Amit
Abstract|A new methodof model registration is proposed
using graphical templates. A decomposable graph of land-
marks is chosen in the template image. All possible candi-
dates for these landmarks are found in the data image using
robust relational local operators. A dynamic programming
algorithm on the template graph nds the optimal match
to a subset of the candidate points in polynomial time. This
combination of local operators to describe points of inter-
est/landmarks and a graph to describe their geometric ar-
rangement 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 MR axial and sagittal images of
the brain to identify speci c anatomies.
Keywords|Key words: Shape and object representation,

  

Source: Amit, Yali - Departments of Computer Science & Statistics, University of Chicago

 

Collections: Computer Technologies and Information Sciences