GA Based Neuro Fuzzy Techniques for Breast Cancer Identification
Arpita Das, Mahua Bhattacharya · 2008
An intelligent computer-aided diagnostics system may be developed to assist the radiologists to recognize the masses/lesions appearing in breast in different groups of benignancy/malignancy. In present work we have attempted to develop a computer assisted treatment planning system implementing Genetic algorithm-based Neuro-fuzzy approaches. The boundary based features of the tumor lesions appearing in breast have been extracted for classification. The shape features represented by Fourier Descriptors, introduce a large number of feature vectors. Thus to classify different boundaries, a standard classifier needs a large number of inputs, and simultaneously to train the classifier a large number of training cycles are required. This may invite the problem of overlearning, followed by chance of misclassification. In proposed methodology, Genetic Algorithm (GA) has been used for searching of significant input feature vectors. Finally adaptive neuro fuzzy-based classifier has been introduced for classification of tumor masses in breast.