A MUTUAL REFERENCE SHAPE BASED ON INFORMATION THEORY

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TitreA MUTUAL REFERENCE SHAPE BASED ON INFORMATION THEORY
Type de publicationConference Paper
Year of Publication2014
AuteursJehan-Besson S., Tilmant C., de Cesare A., Lalande A., Cochet A., Cousty J., Lebenberg J., Lefort M., Clarysse P., Clouard R., Najman L., Sarry L., Frouin F., Garreau M.
Conference Name2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
PublisherIEEE
Conference Location345 E 47TH ST, NEW YORK, NY 10017 USA
ISBN Number978-1-4799-5751-4
Mots-clésActive contours, average shape, cardiac MRI, segmentation evaluation, shape gradient
Résumé

In this paper, we consider the estimation of a reference shape from a set of different segmentation results using both active contours and information theory. The reference shape is defined as the minimum of a criterion that benefits from both the mutual information and the joint entropy of the input segmentations and is then called a mutual shape. This energy criterion is here justified using similarities between information theory quantities and area measures, and presented in a continuous variational framework. This framework brings out some interesting evaluation measures such as the specificity and sensitivity. In order to solve this shape optimization problem, shape derivatives are computed for each term of the criterion and interpreted as an evolution equation of an active contour. Some synthetical examples allow us to cast the light on the difference between our mutual shape and an average shape. Our framework has been considered for the estimation of a mutual shape for the evaluation of cardiac segmentation methods in MRI.