Myocardial Infarct Segmentation and Reconstruction from 2D Late-Gadolinium Enhanced Magnetic Resonance Images
In this paper, we propose a convex optimization-based algorithm for segmenting myocardial infarct from clinical 2D late-gadolinium enhanced magnetic resonance (LGE-MR) images. Previously segmented left ventricular (LV) myocardium was used to define a region of interest for the infarct segmentation. The infarct segmentation problem was formulated as a continuous min-cut problem, which was solved using its dual formulation, the continuous max-flow (CMF). Bhattacharyya intensity distribution matching was used as the data term, where the prior intensity distributions were computed based on a training data set LGE-MR images from seven patients. The algorithm was parallelized and implemented in a graphics processing unit for reduced computation time. Three-dimensional (3D) volumes of the infarcts were then reconstructed using an interpolation technique we developed based on logarithm of odds. The algorithm was validated using LGE-MR images from 47 patients (309 slices) by comparing computed 2D segmentations and 3D reconstructions to manually generated ones. In addition, the developed algorithm was compared to several previously reported segmentation techniques. The CMF algorithm outperformed the previously reported methods in terms of Dice similarity coefficient.
KeywordsImage Segmentation Convex Optimization
- 2.Schmidt, A., Azevedo, C.F., Cheng, A., Gupta, S.N., Bluemke, D.A., Foo, T.K., et al.: Infarct tissue heterogeneity by magnetic resonance imaging identifies enhanced cardiac arrhythmia susceptibility in patients with left ventricular dysfunction. Circulation 115(15), 2006–2014 (2007)CrossRefGoogle Scholar
- 5.Rajchl, M., Yuan, J., White, J., Ukwatta, E., Stirrat, J., Nambakhsh, C., et al.: Interactive hierarchical max-flow segmentation of scar tissue from late-enhancement cardiac MR images. IEEE TMI 33(1), 159–172 (2013)Google Scholar
- 6.Flett, A.S., Hasleton, J., Cook, C., Hausenloy, D., Quarta, G., Ariti, C., et al.: Evaluation of techniques for the quantification of myocardial scar of differing etiology using cardiac magnetic resonance. JACC: CI 4(2), 150–156 (2011)Google Scholar
- 7.Yuan, J., Ukwatta, E., Tai, X.C., Fenster, A., Schnoerr, C.: A fast global optimization-based approach to evolving contours with generic shape prior. Technical report CAM-12-38, UCLA (2012)Google Scholar
- 11.Pohl, K.M., Fisher, J., Bouix, S., Shenton, M., McCarley, R.W., Grimson, W.E.L., et al.: Using the logarithm of odds to define a vector space on probabilistic atlases. MeDIA 11(5), 465–477 (2007)Google Scholar