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A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images
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| Zeitschriftentitel: | Journal of Artificial Intelligence and Soft Computing Research |
|---|---|
| Personen und Körperschaften: | , |
| In: | Journal of Artificial Intelligence and Soft Computing Research, 3, 2013, 4, S. 265-276 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Walter de Gruyter GmbH
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| Schlagwörter: |
| author_facet |
Karimi, Behnam Krzyżak, Adam Karimi, Behnam Krzyżak, Adam |
|---|---|
| author |
Karimi, Behnam Krzyżak, Adam |
| spellingShingle |
Karimi, Behnam Krzyżak, Adam Journal of Artificial Intelligence and Soft Computing Research A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images Artificial Intelligence Computer Vision and Pattern Recognition Hardware and Architecture Modeling and Simulation Information Systems |
| author_sort |
karimi, behnam |
| spelling |
Karimi, Behnam Krzyżak, Adam 2083-2567 Walter de Gruyter GmbH Artificial Intelligence Computer Vision and Pattern Recognition Hardware and Architecture Modeling and Simulation Information Systems http://dx.doi.org/10.2478/jaiscr-2014-0019 <jats:title>Abstract</jats:title> <jats:p>In this research, a new method for automatic detection and classification of suspected breast cancer lesions using ultrasound images is proposed. In this fully automated method, de-noising using fuzzy logic and correlation among ultrasound images taken from different angles is used. Feature selection using combination of sequential backward search, sequential forward search and distance-based methods is obtained. A new segmentation method based on automatic selection of seed points and region growing is proposed and classification of lesions into two malignant and benign classes using combination of AdaBoost, Artificial Neural Network and Fuzzy Support Vector Machine classifiers and majority voting is implemented.</jats:p> A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images Journal of Artificial Intelligence and Soft Computing Research |
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Journal of Artificial Intelligence and Soft Computing Research |
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| title |
A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| title_unstemmed |
A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| title_full |
A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| title_fullStr |
A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| title_full_unstemmed |
A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| title_short |
A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| title_sort |
a novel approach for automatic detection and classification of suspicious lesions in breast ultrasound images |
| topic |
Artificial Intelligence Computer Vision and Pattern Recognition Hardware and Architecture Modeling and Simulation Information Systems |
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http://dx.doi.org/10.2478/jaiscr-2014-0019 |
| publishDate |
2013 |
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265-276 |
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<jats:title>Abstract</jats:title>
<jats:p>In this research, a new method for automatic detection and classification of suspected breast cancer lesions using ultrasound images is proposed. In this fully automated method, de-noising using fuzzy logic and correlation among ultrasound images taken from different angles is used. Feature selection using combination of sequential backward search, sequential forward search and distance-based methods is obtained. A new segmentation method based on automatic selection of seed points and region growing is proposed and classification of lesions into two malignant and benign classes using combination of AdaBoost, Artificial Neural Network and Fuzzy Support Vector Machine classifiers and majority voting is implemented.</jats:p> |
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| description | <jats:title>Abstract</jats:title> <jats:p>In this research, a new method for automatic detection and classification of suspected breast cancer lesions using ultrasound images is proposed. In this fully automated method, de-noising using fuzzy logic and correlation among ultrasound images taken from different angles is used. Feature selection using combination of sequential backward search, sequential forward search and distance-based methods is obtained. A new segmentation method based on automatic selection of seed points and region growing is proposed and classification of lesions into two malignant and benign classes using combination of AdaBoost, Artificial Neural Network and Fuzzy Support Vector Machine classifiers and majority voting is implemented.</jats:p> |
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| spelling | Karimi, Behnam Krzyżak, Adam 2083-2567 Walter de Gruyter GmbH Artificial Intelligence Computer Vision and Pattern Recognition Hardware and Architecture Modeling and Simulation Information Systems http://dx.doi.org/10.2478/jaiscr-2014-0019 <jats:title>Abstract</jats:title> <jats:p>In this research, a new method for automatic detection and classification of suspected breast cancer lesions using ultrasound images is proposed. In this fully automated method, de-noising using fuzzy logic and correlation among ultrasound images taken from different angles is used. Feature selection using combination of sequential backward search, sequential forward search and distance-based methods is obtained. A new segmentation method based on automatic selection of seed points and region growing is proposed and classification of lesions into two malignant and benign classes using combination of AdaBoost, Artificial Neural Network and Fuzzy Support Vector Machine classifiers and majority voting is implemented.</jats:p> A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images Journal of Artificial Intelligence and Soft Computing Research |
| spellingShingle | Karimi, Behnam, Krzyżak, Adam, Journal of Artificial Intelligence and Soft Computing Research, A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images, Artificial Intelligence, Computer Vision and Pattern Recognition, Hardware and Architecture, Modeling and Simulation, Information Systems |
| title | A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| title_full | A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| title_fullStr | A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| title_full_unstemmed | A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| title_short | A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| title_sort | a novel approach for automatic detection and classification of suspicious lesions in breast ultrasound images |
| title_unstemmed | A Novel Approach for Automatic Detection and Classification of Suspicious Lesions in Breast Ultrasound Images |
| topic | Artificial Intelligence, Computer Vision and Pattern Recognition, Hardware and Architecture, Modeling and Simulation, Information Systems |
| url | http://dx.doi.org/10.2478/jaiscr-2014-0019 |