This paper presents an approach to automatic detection of liver tumor in CT images by using region-growing and Support Vector Machine (SVM) which is successfully classifies the liver cancer types such as hepatoma, hemangioma and carcinoma.The method rectifies the problem of manual segmentation and classification which is time consuming due to the variance in the characteristics of CT images.Our proposed method has been tested on a group of CT images obtained from hospitals in Kerala with a promising results both in liver and tumor segmentation. The average error rate and accuracy rate obtained from our proposed method is 0.02 and 0.9.

Region-growing,preprocessing,feature extraction,Segmentation, SVM Classifier.

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