Abstract
This paper introduces a fully automated segmentation scheme for carotid artery ultrasound images. The proposed scheme is based on fuzzy c-means clustering. It consists of four major stages. These stages are pre-processing, feature extraction, fuzzy c-means clustering, and finally boundary extraction. Experimental results demonstrated the efficiency of the proposed scheme in segmenting carotid artery ultrasound images.
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Mao, F., Gill, J., Downey, D., Fenster, A.: Segmentation of carotid artery in ultrasound images. In: Proceedings of the 22nd IEEE Annual International Conference on Engineering in Medicine and Biology Society, July 2000, vol. 3, pp. 1734–1737 (2000)
Abolmaesumi, P., Sirouspour, M., Salcudean, S.: Real-time extraction of carotid artery contours from ultrasound images. In: Proceedings of the 13th IEEE Symposium on Computer-Based Medical Systems, June 2000, pp. 81–186 (2000)
Da-chuan, C., Schmidt-Trucksass, A., Kuo-Sheng, C., Sandrock, M., Qin, P., Burkhardt, H.: Automatic detection of the intimal and the adventitial layers of the common carotid artery wall in ultrasound B-mode images using snakes. In: Proceedings of the International Conference on Image Analysis and Processing, September 1999, pp. 452–457 (1999)
Cohen, L.: On active contour models and balloons. Computer Vision, Graphics, and Image Processing: Image Understanding 53(2), 211–218 (1991)
Neuenschwander, W., Fua, P., Iverson, L., Szekely, G., Kubler, O.: Ziplock snake. International Journal of Computer Vision 25(3), 191–201 (1997)
Hamou, A., El-Sakka, M.: A novel segmentation technique for carotid ultrasound images. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, May 2004, vol. 3, pp. 521–524 (2004)
Canny, J.: Computational Approach To Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6), 679–698 (1986)
Abdel-Dayem, A., El-Sakka, M.: A novel morphological-based carotid artery contour extraction. In: Proceedings of the Canadian Conference on Electrical and Computer Engineering, May 2004, vol. 2, pp. 1873–1876 (2004)
Abdel-Dayem, A., El-Sakka, M., Fenster, A.: Watershed segmentation for carotid artery ultrasound images. In: Proceedings of the IEEE International Conference on Computer Systems and Applications, January 2005 (2005)
Vincent, L., Soille, P.: Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE Transactions on Pattern Analysis and Machine Intelligence 13(6), 583–598 (1991)
Abdel-Dayem, A., El-Sakka, M.: Carotid Artery Contour Extraction from Ultrasound Images Using Multi-Resolution-Analysis and Watershed Segmentation Scheme. ICGST International Journal on Graphics, Vision and Image Processing 5(9), 1–10 (2005)
Abdel-Dayem, A., El-Sakka, M.: Carotid Artery Ultrasound Image Segmentation Using Fuzzy Region Growing. In: Kamel, M., Campilho, A. (eds.) ICIAR 2005. LNCS, vol. 3656, pp. 869–878. Springer, Heidelberg (2005)
Abdel-Dayem, A., El-Sakka, M.: Multi-Resolution Segmentation Using Fuzzy Region Growing for Carotid Artery Ultrasound Images. In: Proceedings of the IEEE International Computer Engineering Conference, 8 pages (December 2006)
Gonzalez, G., Woods, E.: Digital image processing, 2nd edn. Prentice Hall, Englewood Cliffs (2002)
Duda, R., Hart, P., Stork, D.: Pattern Classification, ch. 2, 2nd edn., pp. 20–63. John Wiley & Sons, Chichester (2001)
Bezdek, J.: Fuzzy mathematics in pattern classification. Ph.D. thesis, Applied Mathematic Center, Cornell University, Ithaca, NY (1973)
Kass, M., Witkin, A., Terzopoulos, D.: Snakes: active contour models. In: Proceedings of the 1st International Conference on Computer Vision, pp. 259–268. IEEE Computer Society Press, Los Alamitos (1987)
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Abdel-Dayem, A.R., El-Sakka, M.R. (2007). Fuzzy C-Means Clustering for Segmenting Carotid Artery Ultrasound Images. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2007. Lecture Notes in Computer Science, vol 4633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74260-9_83
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DOI: https://doi.org/10.1007/978-3-540-74260-9_83
Publisher Name: Springer, Berlin, Heidelberg
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