Advanced Segmentation Techniques Using Genetic Algorithm for Recognition of Lung Diseases from CT Scans of Thorax
نویسندگان
چکیده
In this study, texture based segmentation and recognition of the lung diseases from the computed tomography images are presented. The texture based features are extracted by Gabor filtering, feature selection techniques such as Information Gain, Principal Component Analysis, correlation based feature selection are employed with Genetic algorithm which is used as an optimal initialisation of the clusters. The feature outputs are combined by watershed segmentation and the fuzzy C means clustering. The images are recognized with the statistical and the shape based features. The four classes of the dataset of lung diseases are considered and the training and testing are done by the Naive Bayes classifier to classify the datasets. Results of this work show an accuracy of above 90% for the correlation based feature selection method for the four classes of the
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