Abdominal tumor characterization and recognition using superior-order cooccurrence matrices, based on ultrasound images (Q764151)

Summary: The noninvasive diagnosis of malignant tumors is an important issue in research nowadays. Our purpose is to elaborate computerized, texture-based methods for performing computer-aided characterization and automatic diagnosis of these tumors, using only the information from ultrasound images. We consider some of the most frequent abdominal malignant tumors: the hepatocellular carcinoma and the colonic tumors. We compare these structures with the benign tumors and with other visually similar diseases. Besides the textural features that proved in our previous research to be useful in the characterization and recognition of malignant tumors, we improved our method by using the grey level cooccurrence matrix and the edge orientation cooccurrence matrix of superior order. As resulted from our experiments, the new textural features increased the malignant tumor classification performance, also revealing visual and physical properties of these structures that emphasized the complex, chaotic structure of the corresponding tissue.