DocumentCode :
725072
Title :
Corpus callosum thickness estimation using elastic shape matching
Author :
Ayers, Brandon ; Luders, Eileen ; Cherbuin, Nicolas ; Joshi, Shantanu H.
Author_Institution :
Dept. of Comput. & Syst. Biol., Univ. of California at Los Angeles, Los Angeles, CA, USA
fYear :
2015
fDate :
16-19 April 2015
Firstpage :
1518
Lastpage :
1521
Abstract :
We present a shape-based approach for calculating the thickness of the corpus callosum. The corpus callosum is delineated from the MRI midsagittal white matter boundary and represented as a parameterized curve consisting of the top and bottom boundaries by a trained expert. The top and bottom boundaries are first represented in a quotient space of open curves, and then elastically matched under a geometric framework that generates an optimal correspondence between their “shapes”. This matching is computed using a geodesic between shape representations that are invariant to reparameterizations of the curves. Callosal thickness is given by the distance between matched points on the top and bottom boundaries. Our results within a healthy population of N = 96 subjects show significant differences in callosal thickness computed using elastic matching compared to the direct Euclidean approach.
Keywords :
biomedical MRI; differential geometry; image matching; image representation; medical image processing; neurophysiology; thickness measurement; MRI midsagittal white matter boundary; corpus callosum thickness estimation; direct Euclidean approach; elastic shape matching; geodesics; geometric framework; shape representations; Estimation; Geometry; Length measurement; Magnetic resonance imaging; Shape; Thickness measurement; Riemannian metric; corpus callosum; elastic matching; geodesics; shape analysis; thickness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
Conference_Location :
New York, NY
Type :
conf
DOI :
10.1109/ISBI.2015.7164166
Filename :
7164166
Link To Document :
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