Abstract
The objective of this paper is to remove noises of image based on the heuristic noises filter and to automatically detect seed points of tumor region by using K-MEANS in breast ultrasound. The proposed method is to use 4 different kinds of process. First process is the pixel value which indicates the light and shade of image is acquired as matrix type. Second process is an image preprocessing phase that is aimed to maximize a contrast of image and to prevent a leak of personal information. The next process is the heuristic noise filter which is based on the opinion of medical specialist and it is applied to remove noises. The last process is to detect a seed point automatically by applying K-MEANS algorithm. As a result, the noise is effectively eliminated in all images and an automated detection is possible by determining seed points on each tumor.
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© 2009 Springer-Verlag Berlin Heidelberg
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Koo, LJ., Ko, MS., Jo, HW., Park, SC., Wang, GN. (2009). Seed Point Detection of Multiple Cancers Based on Empirical Domain Knowledge and K-means in Ultrasound Breast Image. In: Deng, H., Wang, L., Wang, F.L., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2009. Lecture Notes in Computer Science(), vol 5855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05253-8_56
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DOI: https://doi.org/10.1007/978-3-642-05253-8_56
Publisher Name: Springer, Berlin, Heidelberg
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