Meaningful Features for Computerized Detection of Breast Cancer
نویسندگان
چکیده
After pre-processing and segmenting suspicious masses in mammographies based on the Top-Hat and Markov Random Fields methods, we developed a mass-detection algorithm that uses gray level cooccurrence matrices, gray level difference statistics, gray level run length statistics, shape descriptors and intensity parameters as the entry of a vector support machine classifier. During the classification process we test up to 63 image features, keeping the 35 most important and obtaining 85% of accuracy score.
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