Abstract
We introduce a new multi-region model for simultaneous segmentation of the left and right ventricles, myocardium and the left ventricular papillary muscles in MRI. The model enforces geometric constraints such as inclusion and exclusion between the regions, which makes it possible to correctly segment different regions even though the intensity distributions are identical. We efficiently optimize the model using Lagrangian duality which is faster and more memory efficient than current state of the art. As the optimization is based on global techniques, the resulting segmentations are independent of initialization. We evaluate our approach on two benchmarks with competitive results.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
MICCAI Cardiac MR Left Ventricle Segmentation Challenge (2009), http://smial.sri.utoronto.ca/LV_Challenge/Home.html
Boykov, Y., Jolly, M.: Interactive Organ Segmentation Using Graph Cuts. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 276–286. Springer, Heidelberg (2000)
Boykov, Y., Kolmogorov, V.: Computing geodesics and minimal surfaces via graph cuts. In: ICCV (2003)
Boykov, Y., Kolmogorov, V.: An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. PAMI (2004)
Delong, A., Boykov, Y.: Globally optimal segmentation of multi-region objects. In: ICCV (2009)
Grady, L., Jolly, M.: Weights and Topology: A Study of the Effects of Graph Construction on 3D Image Segmentation. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 153–161. Springer, Heidelberg (2008)
Heiberg, E., et al.: Design and validation of Segment- freely available software for cardiovascular image analysis. BMC Medical Imaging 10(1), 1 (2010)
Kohli, P., Torr, P.: Dynamic graph cuts for efficient inference in markov random fields. PAMI (2007)
Kolmogorov, V., Zabih, R.: What energy functions can be minimized via graph cuts? PAMI (2004)
Lin, X., Cowan, B., Young, A.: Model-based graph cut method for segmentation of the left ventricle. In: IEEE-EMBS (2006)
Lorenzo-Valdés, M., et al.: Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm. Medical Image Analysis 8(3), 255–265 (2004)
Mitchell, S., et al.: Multistage hybrid active appearance model matching: segmentation of left and right ventricles in cardiac MR images. IEEE Transactions on Medical Imaging 20(5), 415–423 (2002)
Nesterov, Y.: Introductory Lectures on Convex Optimization. Kluwer Academic Publishers (2004)
Paragios, N.: A variational approach for the segmentation of the left ventricle in cardiac image analysis. Int. Journal Computer Vision 50(3), 345–362 (2002)
Rother, C., Kolmogorov, V., Lempitsky, V., Szummer, M.: Optimizing binary MRFs via extended roof duality. In: CVPR (2007)
Strandmark, P., Kahl, F.: Parallel and Distributed Graph Cuts by Dual Decomposition. In: CVPR (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ulén, J., Strandmark, P., Kahl, F. (2012). Optimization for Multi-Region Segmentation of Cardiac MRI. In: Camara, O., Konukoglu, E., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2011. Lecture Notes in Computer Science, vol 7085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28326-0_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-28326-0_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28325-3
Online ISBN: 978-3-642-28326-0
eBook Packages: Computer ScienceComputer Science (R0)