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Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images
- Source :
- Computational and Mathematical Methods in Medicine, Computational and Mathematical Methods in Medicine, Vol 2012 (2012)
- Publication Year :
- 2012
- Publisher :
- Hindawi Publishing Corporation, 2012.
-
Abstract
- 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.
- Subjects :
- Pathology
medicine.medical_specialty
Edge orientation
Carcinoma, Hepatocellular
Article Subject
lcsh:Computer applications to medicine. Medical informatics
General Biochemistry, Genetics and Molecular Biology
Matrix (mathematics)
Image Interpretation, Computer-Assisted
medicine
Humans
Ultrasonography
Models, Statistical
General Immunology and Microbiology
business.industry
Applied Mathematics
Ultrasound
Pattern recognition
General Medicine
Kidney Neoplasms
Modeling and Simulation
Abdominal tumor
lcsh:R858-859.7
Grey level
Artificial intelligence
business
Colorectal Neoplasms
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 1748670X
- Database :
- OpenAIRE
- Journal :
- Computational and Mathematical Methods in Medicine
- Accession number :
- edsair.doi.dedup.....a941b46574308cdf7a24fee5e5eda2a1
- Full Text :
- https://doi.org/10.1155/2012/348135