Abstract
Semi-automatic segmentation of the myocardium in 3D echographic images may substantially support clinical diagnosis of heart disease. Particularly in children with congenital heart disease, segmentation should be based on the echo features solely since a priori knowledge on the shape of the heart cannot be used. Segmentation of echocardiographic images is challenging because of the poor echogenicity contrast between blood and the myocardium in some regions and the inherent speckle noise from randomly backscattered echoes. Phase information present in the radio frequency (rf) ultrasound data might yield useful, additional features in these regions. A semi-3D technique was used to determine maximum temporal cross-correlation values locally from the rf data. To segment the endocardial surface, maximum cross-correlation values were used as additional external force in a deformable model approach and were tested against and combined with adaptive filtered, demodulated rf data. The method was tested on full volume images (Philips, iE33) of four healthy children and evaluated by comparison with contours obtained from manual segmentation.
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Noble, J.A., Boukerroui, D.: Ultrasound Image Segmentation: A Survey. IEEE Trans. Med. Imag. 25(8), 987–1010 (2006)
Bosch, J.G., Mitchell, S.C., Lelieveldt, B.P., Nijland, F., Kamp, O., Sonka, M., Reiber, J.H.: Automatic segmentation of echocardiographic sequences by active appearance motion models. IEEE Trans. Med. Imag. 21(11), 1374–1383 (2002)
Boukerroui, D., Basset, O., Baskurt, A., Giminez, G.: A multiparametric and multiresolution segmentation algorithm of 3-D ultrasonic data. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 48(1), 64–77 (2001)
Davignon, F., Deprez, J.F., Basset, O.: A parametric imaging approach for the segmentation of ultrasound data. Ultrasonics 43(10), 789–801 (2005)
Dydenko, I., Friboulet, D., Gorce, J.M., D’Hooge, J., Bijnens, B., Magnin, I.E.: Towards ultrasound cardiac image segmentation based on the radiofrequency signal. Med. Image Anal. 7(3), 353–367 (2003)
Yan, P., Jia, C.X., Sinusas, A., Thiele, K., O’Donnell, M., Duncan, J.S.: LV segmentation through the analysis of radio frequency ultrasonic images. Inf. Process Med. Imaging 20, 233–244 (2007)
Nillesen, M.M., Lopata, R.G.P., Gerrits, I.H., Kapusta, L., Huisman, H.J., Thijssen, J.M., de Korte, C.L.: Segmentation of the heart muscle in 3D pediatric echocardiographic images. Ultrasound Med. Biol. 33(9), 1453–1462 (2007)
Chen, X., Xie, H., Erkamp, R., Kim, K., Jia, C., Rubin, J.M., O’Donnell, M.: 3-D correlation-based speckle tracking. Ultrason Imaging 27(1), 21–36 (2005)
Lopata, R.G.P., Nillesen, M.M., Gerrits, I.H., Thijssen, J.M., Kapusta, L., de Korte, C.L.: 4D cardiac strain imaging: methods and initial results. In: Proceedings of the IEEE International Ultrasonics Symposium, New York, U.S.A., pp. 872–875 (2007)
Delingette, H.: General object reconstruction based on simplex meshes. International Journal of Computer Vision 32(2), 111–146 (1999)
Böttger, T., Kunert, T., Meinzer, H.P., Wolf, I.: Application of a new segmentation tool based on interactive simplex meshes to cardiac images and pulmonary MRI data. Acad. Radiol. 14(3), 319–329 (2007)
Nillesen, M.M., Lopata, R.G.P., de Boode, W.P., Gerrits, I.H., Huisman, H.J., Thijssen, J.M., Kapusta, L., de Korte, C.L.: In vivo validation of cardiac output assessment in non-standard 3D echocardiographic images. Phys. Med. Biol. 54(7), 1951–1962 (2009)
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Nillesen, M.M., Lopata, R.G.P., Huisman, H.J., Thijssen, J.M., Kapusta, L., de Korte, C.L. (2009). 3D Cardiac Segmentation Using Temporal Correlation of Radio Frequency Ultrasound Data. 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_112
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