Abstract
In this paper we propose a novel approach to ventricular motion estimation and segmentation. Our method is based on a MRF formulation where an optimal intensity-based separation between the endocardium and the rest of the cardiac volume is to be determined. Such a term is defined in the spatiotemporal domain, where the ventricular wall motion is introduced to account for correspondences between the consecutive segmentation maps. The estimation of the deformations is done through a continuous deformation field (FFD) where the displacements of the control points are determined using discrete labeling approach. Principles from linear programming and in particular the Primal/Dual Schema is used to recover the optimal solution in both spaces. Promising experimental results obtained on 13 MR spatiotemporal data sets demonstrate the potentials of our method.
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
Shi, P., Sinusas, A.J., Constable, R.T., Ritman, E., Duncan, J.S.: Point-tracked quantitative analysis of left ventricular surface motion from 3d image sequences. IEEE Trans. Med. Imaging 19(1), 36–50 (2000)
McInerney, T., Terzopoulos, D.: Deformable models in medical images analysis: a survey. Medical Image Analysis 1(2), 91–108 (1996)
Paragios, N.: A variational approach for the segmentation of the left ventricle in cardiac image analysis. Int. J. Comput. Vision 50(3), 345–362 (2002)
Jolly, M.-P.: Automatic segmentation of the left ventricle in cardiac mr and ct images. Int. J. Comput. Vision 70(2), 151–163 (2006)
Sermesant, M., Forest, C., Pennec, X., Delingette, H., Ayache, N.: Deformable biomechanical bodels: Application to 4D cardiac image analysis. Medical Image Analysis 7(4), 475–488 (2003)
Montillo, A., Metaxas, D.N., Axel, L.: Automated model-based segmentation of the left and right ventricles in tagged cardiac mri. In: MICCAI, vol. 1, pp. 507–515 (2003)
Guttman, M.A., Prince, J.L., McVeigh, E.R.: Tag and contour detection in tagged mr images of the left ventricle. IEEE Trans. Med. Imaging 13(1), 74–88 (1994)
McEachen II, J.C., Duncan, J.S.: Shape-based tracking of left ventricular wall motion. IEEE Trans. Med. Imaging 16(3), 270–283 (1997)
Bosch, J.G., Mitchell, S.C., Lelieveldt, B.P.F., Nijland, F., Kamp, O., Sonka, M., Reiber, J.H.C.: Automatic segmentation of echocardiographic sequences by active appearance motion models. IEEE Trans. Med. Imaging 21(11), 1374–1383 (2002)
Horn, B.K.P., Schunck, B.G.: Determining optical flow. Artif. Intell. 17(1-3), 185–203 (1981)
Sermesant, M., Delingette, H., Ayache, N.: An electromechanical model of the heart for image analysis and simulation. IEEE Trans. Med. Imaging 25(5), 612–625 (2006)
Komodakis, N., Tziritas, G., Paragios, N.: Fast, approximately optimal solutions for single and dynamic mrfs. In: CVPR 2007. IEEE Conference on Computer Vision & Pattern Recognition, IEEE Computer Society Press, Los Alamitos (2007)
Sederberg, T.W., Parry, S.R.: Free-form deformation of solid geometric models. In: SIGGRAPH 1986. Proceedings of the 13th Annual Conference on Computer Graphics and Interactive Techniques, pp. 151–160 (1986)
Glocker, B., Komodakis, N., Paragios, N., Tziritas, G., Navab, N.: Inter and intra-modal deformable registration: Continuous deformations meet efficient optimal linear programming. In: IPMI 2007. Information Processing in Medical Imaging (2007)
Gerig, G., Jomier, M., Chakos, M.: Valmet: A new validation tool for assessing and improving 3d object segmentation. In: Niessen, W.J., Viergever, M.A. (eds.) MICCAI 2001. LNCS, vol. 2208, pp. 516–523. Springer, Heidelberg (2001)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Besbes, A., Komodakis, N., Glocker, B., Tziritas, G., Paragios, N. (2007). 4D Ventricular Segmentation and Wall Motion Estimation Using Efficient Discrete Optimization. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76858-6_19
Download citation
DOI: https://doi.org/10.1007/978-3-540-76858-6_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-76857-9
Online ISBN: 978-3-540-76858-6
eBook Packages: Computer ScienceComputer Science (R0)