Automatic cardiac 4d segmentation using level sets

Authors:
Karl D. Fritscher;Roland Pilgram;Rainer Schubert
Affiliations:
Institute for Biomedical Image Analysis, University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria;Institute for Biomedical Image Analysis, University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria;Institute for Biomedical Image Analysis, University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria
Venue:
FIMH'05 Proceedings of the Third international conference on Functional Imaging and Modeling of the Heart
Year:
2005

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Abstract

For the analysis of shape variations of the heart and the cardiac motion in a clinical environment it is necessary to segment a large amount of data in order to be able to build statistically significant models. Therefore it has been the aim of this project to find and develop methods that allow the creation of a fully automatic segmentation pipeline for the segmentation of endocardium and myocardium in ECG-triggered MRI images. For this purpose a combination of a number of image processing techniques, from the fields of segmentation, modeling and image registration have been used and extended to create a segmentation pipeline that reduces the need for supplementary manual correction of the segmented labels to a minimum.