Abstract
Delayed-enhancement magnetic resonance imaging (DE-MRI) is an effective technique for imaging left ventricular (LV) infarct. Existing techniques for LV infarct segmentation are primarily threshold-based making them prone to high user variability. In this work, we propose a segmentation algorithm that can learn from training images and segment based on this training model. This is implemented as a Markov random field (MRF) based energy formulation solved using graph-cuts. A good agreement was found with the Full-Width-at-Half-Maximum (FWHM) technique.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Flett, A., Hasleton, J., Cook, C., Hausenloy, D., Quarta, G., Ariti, C., Muthurangu, V., Moon, J.: Evaluation of techniques for the quantification of myocardial scar of differing etiology using cardiac magnetic resonance. JACC Cardiovascular Imaging 4(2), 150 (2011)
Amado, L., Gerber, B., Gupta, S., Rettmann, D., Szarf, G., Schock, R., Nasir, K., Kraitchman, D., Lima, J.: Accurate and objective infarct sizing by contrast- enhanced magnetic resonance imaging in a canine myocardial infarction model. Journal of the American College of Cardiology 44(12), 2383–2389 (2004)
Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1222–1239 (2001)
Boykov, Y., Funka-Lea, G.: Graph cuts and efficient nd image segmentation. International Journal of Computer Vision 70(2), 109–131 (2006)
Rother, C., Kolmogorov, V., Blake, A.: Grabcut: Interactive foreground extraction using iterated graph cuts. ACM Transactions on Graphics (TOG) 23, 309–314 (2004)
Song, Z., Tustison, N., Avants, B., Gee, J.C.: Integrated Graph Cuts for Brain MRI Segmentation. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4191, pp. 831–838. Springer, Heidelberg (2006)
van der Lijn, F., den Heijer, T., Breteler, M., Niessen, W.: Hippocampus segmen- tation in MR images using atlas registration, voxel classification, and graph cuts. NeuroImage 43(4), 708–720 (2008)
Boykov, Y.: University of western ontario vision group wiki page. Source code for implementation of the max-flow/min-cut problem (January 2010)
Dice, L.: Measures of the amount of ecologic association between species. Ecology 26(3), 297–302 (1945)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Karim, R. et al. (2013). Infarct Segmentation of the Left Ventricle Using Graph-Cuts. In: Camara, O., Mansi, T., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2012. Lecture Notes in Computer Science, vol 7746. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36961-2_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-36961-2_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36960-5
Online ISBN: 978-3-642-36961-2
eBook Packages: Computer ScienceComputer Science (R0)