Application of active region model for detection of liver cancer

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

Abstrakty

EN

Active region models are methods for automatic image segmentation. The models are able to detect shapes of irregular borders. In the present paper, the method is examined using medical images of liver changed locally by cancer cells.

Słowa kluczowe

EN

snakes; active region; medical image segmentation

PL

węże; czynny region; medyczna segmentacja obrazu

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2011
• Tom: Vol. 17
• Strony: 263--268
• Opis fizyczny: Bibliogr. 11 poz., rys.

Twórcy

autor

Tracz P.

• Institute of Information Technology, Technical University of Lodz, Wolczanska 215, 90-924 Lodz, Poland

autor

Szczepaniak P. S.

autor

Tomczyk A.

Bibliografia

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• [3] GONZALES R.C., WOODS R.E., Digital Image Processing. Prentice-Hall, Inc., 2002.
• [4] IVINS J., PORRILL J., Active Region Models for Segmenting Medical Images. Artificial Intelligence Visio Research Unit, University of Shefield, 1994.
• [5] KASS M., WITKIN W., TERZOPOULOS S., Snakes: Active Contour Models. Int. Journal of Computer Vision, Vol. 1, No. 4, 1988, pp. 321-333.
• [6] MAKHOUL J., FRANCIS K., SCHWARTZ R., WIESCHEDEL R., Performance measures for information extraction, in: Proceedings of DARPA Broadcast News Workshop, Herndon, VA, 1999.
• [7] TOMCZYK A., Image Segmentation using Adaptive Potential Active Contours. in: KURZYŃSKI M., et al. (Eds.), Computer Recognition Systems, Springer-Verlag, Berlin, Heidelberg, 2007, pp. 148-155.
• [8] TOMCZYK A., Active Hypercontours and Contextual Classification. Proceedings of the 5th International Conference on Intelligent Systems Design and Applications – ISDA’2005, IEEE Computer Society Press, Wroclaw, Poland, 2005, pp. 256-261.
• [9] TOMCZYK A., PIETA L., SZCZEPANIAK P.S., Potential Active Contours – Basic Concepts, Mechanisms and Features, in: PIETKA E., KAWA J., (Eds.), Information Technologies in Biomedicine, ASC 47, Springer-Verlag, Berlin, Heidelberg, 2008, pp. 74-84.
• [10] TOMCZYK A., SZCZEPANIAK P.S., On the Relationship between Active Contours and Contextual Classification, in: KURZYŃSKI M., et al. (Eds.), Computer Recognition Systems, Proceedings of the 4th Int. Conference on Computer Recognition Systems – CORES’05, Springer-Verlag, Berlin, Heidelberg, New York, 2005, pp. 303-310.
• [11] TOMCZYK A., SZCZEPANIAK P.S., Adaptive Potential Active Hypercontours, Proceedings of the 8th International Conference on Artificial Intelligence and Soft Computing – ICAISC’2006, Zakopane, Poland, Springer-Verlag, Berlin, Heidelberg, 2006, pp. 692-701.