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- W1497259015 abstract "Breast cancer is one of the leading causes to women mortality in the world. Clusters of Microcalcifications (MCCs) in mammograms can be an important early sign of breast cancer, the detection is important to prevent and treat the disease. Coordinate Logic Filters (CLF), are very efficient in digital signal processing applications, such as noise removal, magnification, opening, closing, skeletonization, and coding, as well as in edge detection, feature extraction, and fractal modelling. This paper presents an edge detector of MCCs in Regions of Interest (ROI) from mammograms using a novel combination. The edge detector consist in the combination of image enhancement by histogram adaptive technique, a Self Organizing Map (SOM) Neural Network and CLF. The experiment results show that the proposed method can locate MCCs edges. Moreover, the proposed method is quantitatively evaluated by Pratt's figure of merit together with two widely used edge detectors and visually compared, achieving the best results." @default.
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- W1497259015 date "2009-01-01" @default.
- W1497259015 modified "2023-10-01" @default.
- W1497259015 title "Edges Detection of Clusters of Microcalcifications with SOM and Coordinate Logic Filters" @default.
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- W1497259015 doi "https://doi.org/10.1007/978-3-642-02478-8_129" @default.
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