The Evaluation of Data sets with Computed Tomography Images using Image Processing Algorithms

ABSTRACT According to the World Health Organization, cancer is leading cause of deaths globally. Among all types cancer, liver cancer has the lowest survivability, with approximately one million deaths each year. Its rising incidence in the past decade is projected to continue which is associated with varying demographic factors. It is essential for medical practitioners to decide a suitable treatment for cancer patients. For this reason cancer cells should be identified correctly. Computed Tomography (CT) Imaging has developed into a significant tool for physicians to identify liver cancer for decays. A computer-aided analysis of liver cancer in CT images is enormously hard due to some imaging parameters. The techniques considered in this paper are Region growing, Otsus Threshold, watershed and K-means clustering segmentation algorithms. These techniques are evaluated and examined for finest results and highest accuracy.