Abstract
This paper describes a system to automatically segment the left ventricle in all slices and all phases of cardiac cine magnetic resonance datasets. After localizing the left ventricle blood pool using motion, thresholding and clustering, slices are segmented sequentially. For each slice, deformable registration is used to align all the phases, candidates contours are recovered in the average image using shortest paths, and a minimal surface is built to generate the final contours. The advantage of our method is that the resulting contours follow the edges in each phase and are consistent over time. We demonstrate using 19 patient examples that the results are very good. The RMS distance between ground truth and our segmentation is only 1.6 pixels (2.7 mm) and the Dice coefficient is 0.89.
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Lorenzo-Valdés, M., Sanchez-Ortiz, G., Elkington, A., Mohiaddin, R., Rueckert, D.: Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm. Medical Image Analysis 8 (2004)
Jolly, M.: Automatic segmentation of the left ventricle in cardiac MR and CT images. International Journal of Computer Vision 70(2) (2006)
Mitchell, S., Lelieveldt, B., van der Geest, R., Bosch, H., Reiber, J., Sonka, M.: Multistage hybrid active appearance model matching: Segmentation of the left and right ventricles in cardiac MR images. IEEE Trans. Medical Imaging 20(5) (2001)
Fradkin, M., Ciofolo, C., Mory, B., Hautvast, G., Breeuwer, M.: Comprehensive segmentation of cine cardiac MR images. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 178–185. Springer, Heidelberg (2008)
Lynch, M., Ghita, O., Whelan, P.F.: Segmentation of the left ventricle of the heart in 3-D+t MRI data using an optimized nonrigid temporal model. IEEE Trans. Medical Imaging 27(2) (2008)
Sun, W., Çetin, M., Chan, R., Willsky, A.: Segmentation of the evolving left ventricle by learning the dynamics. In: ISBI (2008)
Paragios, N.: A level set approach for shape-driven segmentation and tracking of the left ventricle. IEEE Trans. Medical Imaging 22(6) (2003)
Lorenzo-Valdés, M., Sanchez-Ortiz, G.I., Mohiaddin, R.H., Rueckert, D.: Atlas-based segmentation and tracking of 3D cardiac MR images using non-rigid registration. In: Dohi, T., Kikinis, R. (eds.) MICCAI 2002. LNCS, vol. 2488, p. 642. Springer, Heidelberg (2002)
Jolly, M.-P.: Automatic recovery of the left ventricular blood pool in cardiac cine MR images. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 110–118. Springer, Heidelberg (2008)
Jolly, M.P., Grady, L.: 3D general lesion segmentation in CT. In: ISBI (2008)
Hermosillo, G., Chefd’hotel, C., Faugeras, O.: Variational methods for multimodal image matching. International Journal of Computer Vision 50(3) (2002)
Noble, N., Hill, D., Breeuwer, M., Schnabel, J., Hawkes, D., Gerritsen, F., Razavi, R.: Myocardial delineation via registration in a polar coordinate system. In: Dohi, T., Kikinis, R. (eds.) MICCAI 2002. LNCS, vol. 2488, p. 651. Springer, Heidelberg (2002)
Grady, L.: Computing extact discrete minimal surfaces: Extending and solving the shortest path problem in 3D with application to segmentation. In: CVPR (2006)
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Jolly, MP., Xue, H., Grady, L., Guehring, J. (2009). Combining Registration and Minimum Surfaces for the Segmentation of the Left Ventricle in Cardiac Cine MR Images. In: Yang, GZ., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009. MICCAI 2009. Lecture Notes in Computer Science, vol 5762. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04271-3_110
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DOI: https://doi.org/10.1007/978-3-642-04271-3_110
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