Extracting of Liver Abnormalities and Tumors in Medical Magnetic Resonance Imaging and Computed Tomography Scan Images

Abstract

Liver tumor is one of the most dangerous diseases that cause death, so fast and accurate detecting of tumors represents a vital task. The accurate diagnosis depends upon the robust methods that implemented to detect tumors and other abnormalities regions in the tested medical images like: MRI, CT scan and other types of medical images. In this work, hard and soft schemes of clustering and GLCM methods as well as two hybrid techniques are proposed to extract tumors and other abnormalities in MRI and CT scan images of liver. The results showed that all the proposed segmentation techniques succeeded adequately to detect, isolate and extract the abnormalities and tumors in the adopted medical images according to the consultation of the two radiologists. As well as, the results are in good agreement with the radiologist delineation with relative difference ranged from 0.013 to 0.072 percent.