The role of the complex textural microstructure co-occurrence matrices, based on Laws’ features, in the characterization and recognition of some pathological structures, from ultrasound images
The non-invasive diagnosis, based on ultrasound images, is a challenge in nowadays research. We develop computerized, texture-based methods, for automatic and computer assisted diagnosis, using the information obtained from ultrasound images. In this work, we defined the co-occurrence matrix of comp...
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doaj-95b64504350d4124950f0d72620da4532020-11-25T01:09:33ZengInternational Science and Engineering Society, o.s.International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems1805-54432016-03-0152616710.11601/ijates.v5i2.14494The role of the complex textural microstructure co-occurrence matrices, based on Laws’ features, in the characterization and recognition of some pathological structures, from ultrasound imagesDelia Alexandrina Mitrea0Sergiu Nedevschi1Mihail Abrudean2Radu Chifor3Radu Badea4Technical University of Cluj-NapocaTechnical University of Cluj-NapocaTechnical University of Cluj-Napoca, Automation DepartmentDepartment of Preventive Dentistry, Iuliu Hatieganu University of Medicine and PharmacyMedical Imaging Department, Iuliu Hatieganu University of Medicine and PharmacyThe non-invasive diagnosis, based on ultrasound images, is a challenge in nowadays research. We develop computerized, texture-based methods, for automatic and computer assisted diagnosis, using the information obtained from ultrasound images. In this work, we defined the co-occurrence matrix of complex textural microstructures determined by using the Laws’ convolution filters and we experimented it in order to perform the characterization and recognition of some important anatomical and pathological structures, within ultrasound images. These structures were the colorectal tumors and the gingival sulcus, the properties of the latter being important concerning the diagnosis and monitoring of the periodontal disease. We determined the textural model of these structures, using the classical and the newly defined textural features. For the automatic recognition, we used powerful classifiers, such as the Multilayer Perceptron, the Support-Vector Machines, decision-trees based classifiers such as Random Forest and C4.5, respectively AdaBoost in combination with the C4.5 algorithm.http://ijates.org/index.php/ijates/article/view/144 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Delia Alexandrina Mitrea Sergiu Nedevschi Mihail Abrudean Radu Chifor Radu Badea |
spellingShingle |
Delia Alexandrina Mitrea Sergiu Nedevschi Mihail Abrudean Radu Chifor Radu Badea The role of the complex textural microstructure co-occurrence matrices, based on Laws’ features, in the characterization and recognition of some pathological structures, from ultrasound images International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems |
author_facet |
Delia Alexandrina Mitrea Sergiu Nedevschi Mihail Abrudean Radu Chifor Radu Badea |
author_sort |
Delia Alexandrina Mitrea |
title |
The role of the complex textural microstructure co-occurrence matrices, based on Laws’ features, in the characterization and recognition of some pathological structures, from ultrasound images |
title_short |
The role of the complex textural microstructure co-occurrence matrices, based on Laws’ features, in the characterization and recognition of some pathological structures, from ultrasound images |
title_full |
The role of the complex textural microstructure co-occurrence matrices, based on Laws’ features, in the characterization and recognition of some pathological structures, from ultrasound images |
title_fullStr |
The role of the complex textural microstructure co-occurrence matrices, based on Laws’ features, in the characterization and recognition of some pathological structures, from ultrasound images |
title_full_unstemmed |
The role of the complex textural microstructure co-occurrence matrices, based on Laws’ features, in the characterization and recognition of some pathological structures, from ultrasound images |
title_sort |
role of the complex textural microstructure co-occurrence matrices, based on laws’ features, in the characterization and recognition of some pathological structures, from ultrasound images |
publisher |
International Science and Engineering Society, o.s. |
series |
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems |
issn |
1805-5443 |
publishDate |
2016-03-01 |
description |
The non-invasive diagnosis, based on ultrasound images, is a challenge in nowadays research. We develop computerized, texture-based methods, for automatic and computer assisted diagnosis, using the information obtained from ultrasound images. In this work, we defined the co-occurrence matrix of complex textural microstructures determined by using the Laws’ convolution filters and we experimented it in order to perform the characterization and recognition of some important anatomical and pathological structures, within ultrasound images. These structures were the colorectal tumors and the gingival sulcus, the properties of the latter being important concerning the diagnosis and monitoring of the periodontal disease. We determined the textural model of these structures, using the classical and the newly defined textural features. For the automatic recognition, we used powerful classifiers, such as the Multilayer Perceptron, the Support-Vector Machines, decision-trees based classifiers such as Random Forest and C4.5, respectively AdaBoost in combination with the C4.5 algorithm. |
url |
http://ijates.org/index.php/ijates/article/view/144 |
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