Active contour segmentation of disjoint objects applied to medical images

• Autorzy: Pięta Ł. , Tomczyk A. , Szczepaniak P. S.
• Języki publikacji: EN

Abstrakty

EN

Potential contours are methods for automatic image analysis. In the present paper, potential contours adapted in the supervised way are used for segmentation of disjoint objects and examined using medical images.

Słowa kluczowe

EN

image segmentation; potential active contours

PL

segmentacja obrazu

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2008
• Tom: Vol. 12
• Strony: 163--168
• Opis fizyczny: Bibliogr. 12 poz., rys., tab.

Twórcy

autor

Pięta Ł.

• Institute of Computer Science, Technical University of Lodz, ul. Wolczanska 215, 90-924 Lodz, Poland

autor

Tomczyk A.

autor

Szczepaniak P. S.

Bibliografia

• [1] GONZALES R. C., WOODS R. E. (2002): Digital Image Processing. Prentice-Hall, Inc.
• [2] BANKMAN I. N. (Ed.) (2000): Handbook of Medical Imaging. Processing and Analysis. Academic Press, San Diego.
• [3] TOMCZYK A. (2007): Image Segmentation using Adaptive Potential Active Contours. In: Kurzyński, et al. (Eds.): Computer Recognition Systems. Springer-Verlag, Berlin, Heidelberg; 148-155.
• [4] SONKA M., HLAVEC V., BOYLE R. (1994): Image Processing. Analysis and Machine Vision. Chapman and Hall, Cambridge.
• [5] YONG Y., CHONGXUN Z., PAN L. (2005): A novel Statistical Approach for Segmentation of Single-Channel Brain MRIusing an Improved EM Algorithm. Journal of Appled Computer Science, 13(1), 113-125.
• [6] CASELLES V, KIMMEL R., SAPIRO G. (2000): Geodesic Active Contours. Int. Journal of Computer Vision, vol. 22, no. 1, pp. 61-79.
• [7] KASS M, WITKIN W., TERZOPOULOS S. (1988): Snakes: Active Contour Models. Int. Journal of Computer Vision, vol. 1, no. 4, pp. 321-333.
• [8] TOMCZYK A., SZCZEPANIAK P. S. (2005): On the Relationship between Active Contours and Contextual Classification. In: M.Kurzyński, et al. (Eds.): Computer Recognition Systems. Proceedings of the 4th Int. Conference on Computer Recognition Systems – CORES’05. Springer, Berlin, Heidelberg, New York, pp. 303-310.
• [9] TOMCZYK A. (2005): Active Hypercontours and Contextual Classification. Proceedings of the 5th International Conference on Intelligent Systems Design and Applications – ISDA’2005. Wroclaw, Poland, IEEE Computer Society Press, pp.256-261.
• [10] TOMCZYK A., SZCZEPANIAK P. S. (2006): Adaptive Potential Active Hypercontours. Proceedings of the 8th International Conference on Artificial Intelligence and Soft Computing – ICAISC’2006. Zakopane, Poland. Springer-Verlag, Berlin, Heidelberg; pp. 692-701.
• [11] TOMCZYK A., PIĘTA L., SZCZEPANIAK P. S. (2008): Potential Active Contours – Basic Concepts, Mechanisms and Features. In: E.Pietka, J.Kawa (Eds.): Information Technologies in Biomedicine. ASC 47, Springer-Verlag, Berlin, Heidelberg, 2008; 74-84.
• [12] KIRKPATRICK S., GELATT C. D. (1983): Optimization by Simulated Annealing. Science, 220(4598); 671-680.