Abstract
In this paper a framework for the segmentation of cardiac MR image sequences using spatio-temporal appearance models is presented. The method splits the 4D space into 2 separate subspaces, one for changes in appearance and one subspace for changes in motion. Using the 4D appearance models in combination with a level set framework combines the robustness of model based segmentation with the flexibility of level sets. The method is tested on the first two time frames of 10 cardiac MR sequences leading to promising results. Further tests using a larger training set for the segmentation of the whole cardiac cycle shall be performed in the near future.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Frangi AF, Niessen WJ, Viergever MA. Three-dimensional modeling for functional analysis of cardiac images: A review. IEEE Trans Med Imaging. 2001;20(1):2–25.
Mitchell SC, Bosch JG, Lelieveldt BP, et al. 3-D active appearance models: Segmentation of cardiac MR and ultrasound images. IEEE Trans Med Imaging. 2002;21(9):1167–78.
Mitchell SC, Lelieveldt BP, van der Geest RJ, et al. Multistage hybrid active appearance model matching: segmentation of left and right ventricles in cardiac MR images. IEEE Trans Med Imaging. 2001;20(5):415–23.
Fritscher KD, Grünerbl A, Schubert R. 3D image segmentation using combined shape-intensity prior models. Int J Comp Assist Radiol Surg. 2007;1(6):341–50.
Stegmann MB, Ersboll BK, Larsen R. FAME: A flexible appearance modeling environment. IEEE Trans Med Imaging. 2003;22(10):1319–31.
Perperidis D, Mohiaddin RH, Rueckert D. Spatio-temporal free-form registration of cardiac MR image sequences. Med Image Anal. 2005;9(5):441–56.
von Berg J, Lorenz C. A geometric model of the beating heart. Methods Inf Med. 2007;46(3):282–6.
Montagnat J, Delingette H. 4D deformable models with temporal constraints: Application to 4D cardiac image segmentation. Med Image Anal. 2005;9(1):87–100.
Vercauteren T, Pennec X, Perchant A, et al. Non-parametric diffeomorphic image registration with the demons algorithm. Proc MICCAI. 2007;10(2):319–26.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fritscher, K., Schubert, R. (2008). 4D Endocardial Segmentation Using Spatio-temporal Appearance Models and Level Sets. In: Tolxdorff, T., Braun, J., Deserno, T.M., Horsch, A., Handels, H., Meinzer, HP. (eds) Bildverarbeitung für die Medizin 2008. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78640-5_1
Download citation
DOI: https://doi.org/10.1007/978-3-540-78640-5_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78639-9
Online ISBN: 978-3-540-78640-5
eBook Packages: Computer Science and Engineering (German Language)