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Microcalcifications are one of the key symptoms facilitating early detection of breast cancer. In this paper, The textural features are extracted from the segmented mammogram image to classify the microcalcifications into benign, malignant or normal. The reduced features are selected from the extracted set of features using reduction algorithms. Initially the reduced features are normalized between...
This paper proposes a image enhancement and segmentation method for mammographic images, which is based on the pixel intensity transformation, spatial filtering, edge detection, and region growing techniques. This method consists of two approaches. The first approach is applying intensity transformation, logarithmic transformation, contrast stretching, histogram equalization and spatial filtering...
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