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