Abstract
In this paper, we present a new approach for segmentation of left and right ventricles from cardiac MR images. A two-level-set formulation is proposed which is the extension of distance regularized level set evolution (DRLSE) model in [1], with the 0-level set and k-level set representing the endocardium and epicardium, respectively. The extraction of endocardium and epicardium is obtained as a result of the interactive curve evolution of the 0 and k level sets derived from the proposed variational level set formulation. The initialization of the proposed two-level-set DRLSE model is generated by performing the original DRLSE from roughly located endocardium. Experimental results have demonstrated the effectiveness of the proposed two-level-set DRLSE model.
Keywords
- Distance Regularized Level Set Evolution (DRLSE)
- Right Ventricle Segmentation
- Epicardial Contours
- Desired Object Boundary
- Endocardial Contours
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Li, C., Xu, C., Gui, C., Fox, M.D.: Distance regularized level set evolution and its application to image segmentation. IEEE Trans. Image Process. 19, 3243–3254 (2010)
Paragios, N.: A variational approach for the segmentation of the left ventricle in cardiac image analysis. Int. J. Comput. Vis. 50, 345–362 (2002)
Petitjean, C., Dacher, J.N.: A review of segmentation methods in short axis cardiac MR images. Med. Image Anal. 15, 169–184 (2011)
Kurkure, U., Pednekar, A., Muthupillai, R., Flamm, S.D., Kakadiaris, I.A.: Localization and segmentation of left ventricle in cardiac cine-MR images. IEEE Trans. Biomed. Eng. 56, 1360–1370 (2009)
Qian, X., Lin, Y., Zhao, Y., Wang, J., Liu, J., Zhuang, X.: Segmentation of myocardium from cardiac mr images using a novel dynamic programming based segmentation method. Med. Phys. 42, 1424–1435 (2015)
Frangi, A.F., Niessen, W.J., Viergever, M.A.: Three-dimensional modelling for functional analysis of cardiac images: a review. IEEE Trans. Med. Image 20, 2–5 (2001)
Li, C., Kao, C., Gore, J.C., Ding, Z.: Minimization of region-scalable fitting energy for image segmentation. IEEE Trans. Image Process. 17, 1940–1949 (2008)
Chan, T., Vese, L.: Active contours without edges. IEEE Trans. Image Process. 10, 266–277 (2001)
Qian, X., Wang, J., Guo, S., Li, Q.: An active contour model for medical image segmentation with application to brain ct image. Med. Phys. 40, 8 (2012)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. Int. J. Comput. Vis. 1, 321–331 (1988)
Chen, Y., Tagare, H.D., Thiruvenkadam, S., Huang, F., Wilson, D., Gopinath, K.S., Richard Briggs, W., Geiser, E.A.: Using prior shapes in geometric active contours in a variational framework. IJCV 50, 315–328 (2002)
Leventon, M., Grimson, W., Faugeras, O.: Statistical shape influence in geodesic active contours. In: 2000 Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 316–323 (2000)
Wu, J., Brigham, K.G., Simon, M.A., Brigham, J.C.: An implementation of independent component analysis for 3d statistical shape analysis. Biomed. Sign. Process. Control 13, 345–356 (2014)
Jolly, M.: Automatic segmentation of the left ventricle in cardiac MR and CT images. Int. J. Comput. Vis. 70, 151–163 (2006)
Zuluaga, M.A., Cardoso, M.J., Ourselin, S.: Automatic right ventricle segmentation using multi-label fusion in cardiac mri. In: Workshop on RV Segmentation Challenge in Cardiac MRI Medical Image Computing and Computer-Assisted Intervention (2012)
Bai, W., Shi, W., O’Regan, D., Tong, T., Wang, H., Jamil-Copley, S., Peters, N., Rueckert, D.: A probabilistic patch-based label fusion model for multi-atlas segmentation with registration refinement: Application to cardiac mr images. IEEE Trans. Med. Imaging 32, 1302–1315 (2013)
Ringenberg, J., Deo, M., Devabhaktuni, V., Berenfeld, O., Boyers, P., Gold, J.: Fast, accurate, and fully automatic segmentation of the right ventricle in short-axis cardiac MRI. Comput. Med. Imaging Graph. 38, 190–201 (2014)
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Liu, Y., Zhao, Y., Guo, S., Zhang, S., Li, C. (2015). Edge Based Segmentation of Left and Right Ventricles Using Two Distance Regularized Level Sets. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9475. Springer, Cham. https://doi.org/10.1007/978-3-319-27863-6_19
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DOI: https://doi.org/10.1007/978-3-319-27863-6_19
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