Abstract
This paper proposes a hybrid system which combines computer extracted features and human interpreted features from the mammogram, with the statistical classifier's output as another kind of features in conjunction with a genetic neural network classifier. The hybrid system produced better results than the single statistical classifier and neural network. The highest classification rate reached 91.3%. The area value under the ROC curve is 0.962. The results indicated that the mixed features contribute greatly for the classification of mass patterns into benign and malignant.
Original language | English |
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Pages (from-to) | 316-319 |
Number of pages | 4 |
Journal | Lecture Notes in Computer Science |
Volume | 3614 |
Issue number | PART II |
DOIs | |
Publication status | Published - 2005 |