Abstract
CAD-CTC helps the radiologists for the automatic detection of suspicious polyps in the CT images of the colon. In this paper, a novel method is proposed in order to decrease the computational time taken by the CAD system. In the proposed CAD system, segmentation of the colon is done by Otsu's method of thresholding and clustered by k-means for extraction of the candidates. Classification is performed by SVM (Support Vector Machine) and ANN (Artificial Neural Network) from the training and testing images of candidate extraction. The proposed CAD system is evaluated with 16 slices (each) of normal and abnormal images. The CAD system achieved a minimal computation time (10 minutes) and an increased learning rate of about 1.2608 at an epoch 411.Thus the good results demonstrate that the proposed system may provide relevant additional information
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