Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images
Author(s) -
Delia Mitrea,
Paulina Mitrea,
Sergiu Nedevschi,
Radu Badea,
Monica LupșorPlaton,
Mihai Socaciu,
Adela Golea,
Claudia Hagiu,
Lidia Ciobanu
Publication year - 2012
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2012/348135
Subject(s) - grey level , texture (cosmology) , computer science , radiology , ultrasound , medicine , artificial intelligence , orientation (vector space) , characterization (materials science) , hepatocellular carcinoma , pattern recognition (psychology) , image (mathematics) , mathematics , materials science , geometry , nanotechnology
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.
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