Comparative Study on Feature Extraction Method for Breast Cancer Classification
نویسندگان
چکیده
This paper presents an evaluation and comparison of the performance of three different feature extraction methods for classification of normal and abnormal patterns in mammogram. Three different feature extraction methods used here are intensity histogram, GLCM (Grey Level Co-occurrence Matrix) and intensity based features. A supervised classifier system based on neural network is used. The performance of the each feature extraction method is evaluated on Digital Database for Screening Mammography (DDSM) breast cancer database. The experimental results suggest that GLCM method outperformed the other two methods.
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