Abstract
The presence of speckle in ultrasound images makes it hard to segment them using active contours. Speckle causes the energy function of the active contours to have many local minima, and the gradient descent procedure used for evolving the contour gets trapped in these minima.
A new algorithm, called tunnelling descent, is proposed in this paper for evolving active contours. Tunnelling descent can jump out of many of the local minima that gradient descent gets trapped in. Experimental results with 70 short axis cardiac ultrasound images show that tunnelling descent has no trouble finding the blood-tissue boundary (the endocardium). This holds irrespective of whether tunnelling descent is initialized in blood or tissue.
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References
Basseville, M., Nikiforov, I.V.: Detection of Abrupt Changes, Theory and application. PTR Prentice Hall, Englewood Cliffs (1993)
Tao, Z., Beaty, J., Jaffe, C.C., Tagare, H.D.: Gray level models for segmentating myocardium and blood in cardiac ultrasound images. In: Proceedings ISBI 2002 (2002)
Wagner. R. F., Insana, M. F., Brown, D. G., Statistical properties of radiofrequency and envelope-detected signals with applications to medical ultrasound. J. Opt. Soc. Am. A 4(5), (1987)
Wagner, R.F., Smith, S.W., Sandrick, J.M., Lopez, H.: Statistics of speckles in ultrasound B-scans. IEEE. Trans. Son. Ultra. 30, 156–163 (1983)
Xiao, G., Brady, M., Noble, J., Zhang, Y.: Segmentation of Ultrasound B-Mode images with intensity inhomogeneity correction. IEEE Trans. Medical Imaging 21(1), 48–57 (2002)
Evans, A., Nixon, M.: Biased motion-adaptive temporal filtering for speckle reduction in echocardiography. IEEE Trans. Medical Imaging 15(1), 39–50 (1996)
Zong, X., Laine, A., Geiser, E.: Speckle reduction and contrast enhancement of echocardiograms via multiscale nonlinear processing. IEEE Trans. Medical Imaging 17(4), 532–540 (1998)
Angelini, E.D., Laine, A.F., Takuma, S., Holmes, J.W., Homma, S.: LV volume quantification via spatio temporal analysis of real-time 3-D echocardiography. IEEE Trans. Medical Imaging 20, 457–469 (2001)
Bosch, J., Mitchell, S., Lelieveldt, B., Nijland, F., Kamp, O., Sonka, M., Reober, J.: Fully automated endocardial contour detection in time sequences of echocardiograms by active appearance motion models. Computers in Cardiology 2001, pp. 93–96 (2001)
Hao, X., Bruce, C.J., Pislaru, C., Greenleaf, J.F.: Segmenting high-frequency intracardiac ultrasound images of myocardium into infarcted, ischemic, and normal regions. IEEE Tran. Medical Imaging 20(12), 1371–1383 (2001)
Mulet-Parada, M., Noble, J.A.: Intensity-invariant 2D+T acoustic boundary detection. In: Proceedings, Workshop on Biomedical Image Analysis, June 1998, pp. 133–142 (1998)
Mikic, I., Krucinski, S., Thomas, J.D.: Segmentation and tracking in echocardiographic sequences: active contours guided by optical flow estimates. IEEE Trans. Medical Imaging 17(2), 274–284 (1998)
Wald, A.: Sequential Analysis. Dover Publications, New York
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© 2003 Springer-Verlag Berlin Heidelberg
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Tao, Z., Jaffe, C.C., Tagare, H.D. (2003). Tunnelling Descent: A New Algorithm for Active Contour Segmentation of Ultrasound Images. In: Taylor, C., Noble, J.A. (eds) Information Processing in Medical Imaging. IPMI 2003. Lecture Notes in Computer Science, vol 2732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45087-0_21
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DOI: https://doi.org/10.1007/978-3-540-45087-0_21
Publisher Name: Springer, Berlin, Heidelberg
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