AN ENHANCED LIVER STAGES CLASSIFICATION IN 3D-CT AND 3D-US IMAGES USING GLRLM AND 3D-CNN

Ultrasound (US) and computed tomography (CT) plays a fundamental role in the classification and staging of liver infections. But the most popular technologies 3D-US and 3D-CT make the identification process more accurate. In this paper among the two technologies that give more accurate results are analyzed. In the proposed method Gray Level Run Length Matrix (GLRLM) is used for extracting the features. Region-based segmentation technique is used to segment the affected parts.3D-CNN is used for the staging and classification of Liver 3D-CT and 3D-US Images separately. The results are then analyzed and found that 3D-CT gives higher accuracy than 3D-US. The proposed model is implemented using TensorFlow and Keras of python.