Abstract
In this paper we propose a supervised method for the segmentation of masses in mammographic images. The algorithm starts with a selected pixel inside the mass, which has been manually selected by an expert radiologist. Based on the active region approach, an energy function is defined which integrates texture, contour and shape information. Then, pixels are aggregated or eliminated to the region by optimizing this function allowing to obtain an accurate segmentation. Moreover, a texture feature selection process, performed before the segmentation, ensures a reliable subset of features. Experimental results prove the validity of the proposed method.
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Martí, J., Freixenet, J., Muñoz, X., Oliver, A. (2003). Active Region Segmentation of Mammographic Masses Based on Texture, Contour and Shape Features. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_56
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DOI: https://doi.org/10.1007/978-3-540-44871-6_56
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