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.
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© 2005 Springer-Verlag Berlin Heidelberg
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Fritscher, K.D., Pilgram, R., Schubert, R. (2005). Automatic Cardiac 4D Segmentation Using Level Sets. In: Frangi, A.F., Radeva, P.I., Santos, A., Hernandez, M. (eds) Functional Imaging and Modeling of the Heart. FIMH 2005. Lecture Notes in Computer Science, vol 3504. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494621_12
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DOI: https://doi.org/10.1007/11494621_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26161-2
Online ISBN: 978-3-540-32081-4
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