Decide, Detect and Classify Benign and Malignant in Mammograms Using Cv-partitioning Method

In recent years, the stage determining and classifying the mammogram as Benign or Malignant is somewhat complicated process in the medical research. In the earlier papers many classification techniques, CAD designs and feature extraction methods are used constantly for mammogram classification, and has its own advantages and limitations. To overcome the limitations, in this paper a novel approach is introduced for accurate classification of Benign and Malignant mammogram. This novel approach functions in three stages, where preprocess the image, decide the image in complete normal or Benign/Malignant and Determine whether the mammogram is Benign or Malignant by comparing the shape, color, texture and size of the extracted abnormal part of the mammogram Images. The experiment results give more than 99.3% of accuracy in classification by a MATLAB Programming method. The performance evaluation of the image is compared with the cv-partition method and feature extraction method.