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Full-Text Articles in Engineering
A Neural-Genetic Algorithm For Feature Selection And Breast Abnormality Classification In Digital Mammography, Ping Zhang, Brijesh Verma, Kuldeep Kumar
A Neural-Genetic Algorithm For Feature Selection And Breast Abnormality Classification In Digital Mammography, Ping Zhang, Brijesh Verma, Kuldeep Kumar
Kuldeep Kumar
Digital mammography is one of the most suitable methods for early detection of breast cancer. It uses digital mammograms to find suspicious areas. However, it is very difficult to distinguish benign and malignant cases, especially for the small size lesions in the early stage of cancer. This is reflected in the high percentage of unnecessary biopsies that are performed and many deaths caused by late detection or misdiagnosis. A computer based feature selection and classification system can provide a second opinion to the radiologists. This work proposes a neural-genetic algorithm for feature selection in conjunction with neural network based classifier. …
A Hybrid Classifier For Mass Classification With Different Kinds Of Features In Mammography, Ping Zhang, Kuldeep Kumar, Brijesh Verma
A Hybrid Classifier For Mass Classification With Different Kinds Of Features In Mammography, Ping Zhang, Kuldeep Kumar, Brijesh Verma
Kuldeep Kumar
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 feature 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.
Neural Vs Statistical Classifier In Conjunction With Genetic Algorithm Feature Selection In Digital Mammography, Ping Zhang, Brijesh Verma, Kuldeep Kumar
Neural Vs Statistical Classifier In Conjunction With Genetic Algorithm Feature Selection In Digital Mammography, Ping Zhang, Brijesh Verma, Kuldeep Kumar
Kuldeep Kumar
Digital mammography is one of the most suitable methods for early detection of breast cancer. It uses digital mammograms to find suspicious areas containing benign and malignant microcalcifications. However, it is very difficult to distinguish benign and malignant microcalcifications. This is reflected in the high percentage of unnecessary biopsies that are performed and many deaths caused by late detection or misdiagnosis. A computer based feature selection and classification system can provide a second opinion to the radiologists in assessment of microcalcifications. The research proposes and investigates a neural-genetic algorithm for feature selection in conjunction with neural and statistical classifiers to …