Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images
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...
Main Authors: | , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2012-01-01
|
Series: | Computational and Mathematical Methods in Medicine |
Online Access: | http://dx.doi.org/10.1155/2012/348135 |
id |
doaj-f96554981a88451eb0c2f2dcef5c408f |
---|---|
record_format |
Article |
spelling |
doaj-f96554981a88451eb0c2f2dcef5c408f2020-11-25T00:04:02ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182012-01-01201210.1155/2012/348135348135Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound ImagesDelia Mitrea0Paulina Mitrea1Sergiu Nedevschi2Radu Badea3Monica Lupsor4Mihai Socaciu5Adela Golea6Claudia Hagiu7Lidia Ciobanu8Department of Computer Science, Technical University of Cluj-Napoca, George Baritiu Street 26–28, 400027 Cluj-Napoca, RomaniaDepartment of Computer Science, Technical University of Cluj-Napoca, George Baritiu Street 26–28, 400027 Cluj-Napoca, RomaniaDepartment of Computer Science, Technical University of Cluj-Napoca, George Baritiu Street 26–28, 400027 Cluj-Napoca, RomaniaDepartment of Ultrasonography, Iuliu Hatieganu University of Medicine and Pharmacy, Victor Babeş Street 8, 400079 Cluj-Napoca, RomaniaDepartment of Ultrasonography, Iuliu Hatieganu University of Medicine and Pharmacy, Victor Babeş Street 8, 400079 Cluj-Napoca, RomaniaDepartment of Ultrasonography, Iuliu Hatieganu University of Medicine and Pharmacy, Victor Babeş Street 8, 400079 Cluj-Napoca, RomaniaDepartment of Ultrasonography, Iuliu Hatieganu University of Medicine and Pharmacy, Victor Babeş Street 8, 400079 Cluj-Napoca, RomaniaDepartment of Ultrasonography, Iuliu Hatieganu University of Medicine and Pharmacy, Victor Babeş Street 8, 400079 Cluj-Napoca, RomaniaDepartment of Ultrasonography, Iuliu Hatieganu University of Medicine and Pharmacy, Victor Babeş Street 8, 400079 Cluj-Napoca, RomaniaThe 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.http://dx.doi.org/10.1155/2012/348135 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Delia Mitrea Paulina Mitrea Sergiu Nedevschi Radu Badea Monica Lupsor Mihai Socaciu Adela Golea Claudia Hagiu Lidia Ciobanu |
spellingShingle |
Delia Mitrea Paulina Mitrea Sergiu Nedevschi Radu Badea Monica Lupsor Mihai Socaciu Adela Golea Claudia Hagiu Lidia Ciobanu Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images Computational and Mathematical Methods in Medicine |
author_facet |
Delia Mitrea Paulina Mitrea Sergiu Nedevschi Radu Badea Monica Lupsor Mihai Socaciu Adela Golea Claudia Hagiu Lidia Ciobanu |
author_sort |
Delia Mitrea |
title |
Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images |
title_short |
Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images |
title_full |
Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images |
title_fullStr |
Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images |
title_full_unstemmed |
Abdominal Tumor Characterization and Recognition Using Superior-Order Cooccurrence Matrices, Based on Ultrasound Images |
title_sort |
abdominal tumor characterization and recognition using superior-order cooccurrence matrices, based on ultrasound images |
publisher |
Hindawi Limited |
series |
Computational and Mathematical Methods in Medicine |
issn |
1748-670X 1748-6718 |
publishDate |
2012-01-01 |
description |
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. |
url |
http://dx.doi.org/10.1155/2012/348135 |
work_keys_str_mv |
AT deliamitrea abdominaltumorcharacterizationandrecognitionusingsuperiorordercooccurrencematricesbasedonultrasoundimages AT paulinamitrea abdominaltumorcharacterizationandrecognitionusingsuperiorordercooccurrencematricesbasedonultrasoundimages AT sergiunedevschi abdominaltumorcharacterizationandrecognitionusingsuperiorordercooccurrencematricesbasedonultrasoundimages AT radubadea abdominaltumorcharacterizationandrecognitionusingsuperiorordercooccurrencematricesbasedonultrasoundimages AT monicalupsor abdominaltumorcharacterizationandrecognitionusingsuperiorordercooccurrencematricesbasedonultrasoundimages AT mihaisocaciu abdominaltumorcharacterizationandrecognitionusingsuperiorordercooccurrencematricesbasedonultrasoundimages AT adelagolea abdominaltumorcharacterizationandrecognitionusingsuperiorordercooccurrencematricesbasedonultrasoundimages AT claudiahagiu abdominaltumorcharacterizationandrecognitionusingsuperiorordercooccurrencematricesbasedonultrasoundimages AT lidiaciobanu abdominaltumorcharacterizationandrecognitionusingsuperiorordercooccurrencematricesbasedonultrasoundimages |
_version_ |
1725431435326652416 |