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The paper investigates on recognition of breast abnormalities. A novel feature frame work was proposed on mammographic patches based on both texture and geometric features for classification of breast tissues into normal, malignant and benign. The methodology comprises of five stages. First step is preprocessing, texture feature extraction using Local quinary pattern for classifying breast tissues...
Shape of breast Contours are prominent signs to determine malignancy in mammograms. A new algorithm for feature extraction is proposed based on polynomial regression on the signatures of benign and malignant contours. Two features mean absolute error and correlation coefficient were extracted for 57 mammograms of which 32 images were malignant contours and 25 images were benign contours. Three different...
Early detection of breast cancer is carried out by using mammographic images. Due to low contrast nature of these images, it is difficult to detect signs such as micro calcifications and masses. This paper describes novel algorithms for early detection of breast cancer using image processing techniques. Novel algorithms are implemented for 1) Mass region extraction to get exact shape of the mass 2)...
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