{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T13:28:04Z","timestamp":1767706084626},"reference-count":18,"publisher":"Hindawi Limited","license":[{"start":{"date-parts":[[2012,1,1]],"date-time":"2012-01-01T00:00:00Z","timestamp":1325376000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"name":"Romanian Ministry of Education and Research","award":["PNII-ID-PCE-833\/2008"],"award-info":[{"award-number":["PNII-ID-PCE-833\/2008"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2012]]},"abstract":"<jats:p>The noninvasive diagnosis of the 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. In this paper, we considered some of the most frequent abdominal malignant tumors: the hepatocellular carcinoma and the colonic tumors. We compared 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 the 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.<\/jats:p>","DOI":"10.1155\/2012\/348135","type":"journal-article","created":{"date-parts":[[2012,1,19]],"date-time":"2012-01-19T21:03:38Z","timestamp":1327007018000},"page":"1-17","source":"Crossref","is-referenced-by-count":29,"title":["Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images"],"prefix":"10.1155","volume":"2012","author":[{"given":"Delia","family":"Mitrea","sequence":"first","affiliation":[{"name":"Department of Computer Science, Technical University of Cluj-Napoca, George Baritiu Street 26\u201328, 400027 Cluj-Napoca, 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