Abstract
Real-time three-dimensional (RT3D) echocardiography is a new imaging modality that presents the unique opportunity to visualize the complex three-dimensional (3 -D) shape and the motion of left ventricle (LV) in vivo. To take advantage of this opportunity, automatic segmentation of LV myocardium is essential. While there are a variety of efforts on the segmentation of LV endocardial (ENDO) boundaries, the segmentation of epicardial (EPI) boundaries is still problematic. In this paper, we present a new approach of coupled-surfaces propagation to address this problem. Our method is motivated by the idea that the volume of the myocardium is close to being constant during a cardiac cycle and takes this tight coupling as an important constraint. We employ two surfaces, each driven by the image-derived information that takes into account the ultrasound physics by modeling speckle using shifted Rayleigh distribution while maintaining the coupling. By evolving two surfaces simultaneously, the final representation of myocardium is thus achieved. Results from 328 sets of RT3D echocardiographic data are evaluated against the outlines of three observers. We show that the results from automatic segmentation are comparable to those from manual segmentation.
This work is supported by the grant 5R01HL082640-02.
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Keywords
- Blood Pool
- Automatic Segmentation
- Incompressibility Constraint
- Myocardial Volume
- Left Ventricle Myocardium
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References
Noble, J.A., Boukerroui, D.: Ultrasound image segmentation: A survey. IEEE Trans. Med. Imag. 25(8), 987–1010 (2006)
Malassiotis, S., Strintzis, M.G.: Tracking the left ventricle in echocardiographic images by learning heart dynamics. IEEE Trans. Med. Imag. 8(3), 282–290 (1999)
Dias, J.M.B., Leitao, J.M.N.: Wall position and thickness estimation from sequences of echocardiographic images. IEEE Trans. Med. Imag. 15(1), 25–38 (1996)
Feng, J., Lin, W.C., Chen, C.T.: Epicardial boundary detection using fuzzy reasoning. IEEE Trans. Med. Imag. 10(2), 187–199 (1991)
Lin, N., Yu, W., Duncan, J.S.: Combinative multi-scale level set framework for echocardiographic image segmentation. Med. Imag. Analysis 9(4), 529–537 (2003)
Zeng, X., Staib, L.H., Schultz, R.T., Duncan, J.S.: Segmentation and measurement of cortex from 3d mr images using coupled surfaces propagation. IEEE Trans. Med. Imag. 18(10), 927–937 (1999)
Tao, Z., Tagare, H.D., Beaty, J.D.: Evaluation of four probability distribution models for speckle in clinical cardiac ultrasound images. IEEE Trans. Med. Imag. (11), 1483–1491 (2006)
Goodman, J.W.: Some fundamental properties of speckle. J. Opt. Soc. Amer. 66(11), 1145–1150 (1976)
Chan, T., Vese, L.: Active contours without edges. IEEE Trans. Imag. Proc. 10(2), 266–277 (2001)
Yin, F.C.P., Chan, C.C.H., Juddy, R.M.: Compressibility of perfused passive myocardium. Amer. J. Physiol. - Heart Circ. Physiol. 271(5), 1864–1870 (1996)
Liu, Y.H., Bahn, R.C., Ritman, E.L.: Dynamic intramyocardial blood volume: Evaluation with a radiological opaque marker method. Amer. J. Physiol. - Heart Circ. Physiol. 263(3), 963–967 (1992)
Papademetris, X., Sinusas, A., Dione, D.P., Constable, R.T., Duncan, J.S.: Estimation of 3d left ventricular deformation from 3d medical image sequences using biomechanical models. IEEE Trans. Med. Imag. 21(7), 786–800 (2002)
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Zhu, Y., Papademetris, X., Sinusas, A., Duncan, J.S. (2007). Segmentation of Myocardial Volumes from Real-Time 3D Echocardiography Using an Incompressibility Constraint. In: Ayache, N., Ourselin, S., Maeder, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. MICCAI 2007. Lecture Notes in Computer Science, vol 4791. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75757-3_6
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DOI: https://doi.org/10.1007/978-3-540-75757-3_6
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