Automatic framework for the detection of coronary artery calcification in IVUS images
The paper propose an automatic framework for the detection of coronary artery calcification in intravascular ultrasound (IVUS) images using texture analysis method. The texture features used is called Histogram of Equivalent Patterns (HEPs) Features. Experiments was conducted using 2175 IVUS images,...
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| Format: | Article |
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The Mattingley Publishing Co., Inc.
2020
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| _version_ | 1796865195064164352 |
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| author | Mohammad, S. Sofian, H. Mohd. Noor, Norliza |
| author_facet | Mohammad, S. Sofian, H. Mohd. Noor, Norliza |
| author_sort | Mohammad, S. |
| collection | ePrints |
| description | The paper propose an automatic framework for the detection of coronary artery calcification in intravascular ultrasound (IVUS) images using texture analysis method. The texture features used is called Histogram of Equivalent Patterns (HEPs) Features. Experiments was conducted using 2175 IVUS images, 530 with calcification plague and 1645 without calci-fication plague. The images are from dataset B of MICCAI challenge 2011. The classifier used is 1-NN classifier. A 2-fold cross-validation process is applied to the IVUS image database to evaluate the performance of the proposed framework. The highest accuracy obtained is 95.89 %, using a variant of Com-pleted Local Binary Patterns (CLBP) descriptors as the features. |
| first_indexed | 2024-03-05T20:53:15Z |
| format | Article |
| id | utm.eprints-91273 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T20:53:15Z |
| publishDate | 2020 |
| publisher | The Mattingley Publishing Co., Inc. |
| record_format | dspace |
| spelling | utm.eprints-912732021-06-30T12:07:18Z http://eprints.utm.my/91273/ Automatic framework for the detection of coronary artery calcification in IVUS images Mohammad, S. Sofian, H. Mohd. Noor, Norliza T58.6-58.62 Management information systems The paper propose an automatic framework for the detection of coronary artery calcification in intravascular ultrasound (IVUS) images using texture analysis method. The texture features used is called Histogram of Equivalent Patterns (HEPs) Features. Experiments was conducted using 2175 IVUS images, 530 with calcification plague and 1645 without calci-fication plague. The images are from dataset B of MICCAI challenge 2011. The classifier used is 1-NN classifier. A 2-fold cross-validation process is applied to the IVUS image database to evaluate the performance of the proposed framework. The highest accuracy obtained is 95.89 %, using a variant of Com-pleted Local Binary Patterns (CLBP) descriptors as the features. The Mattingley Publishing Co., Inc. 2020-04 Article PeerReviewed Mohammad, S. and Sofian, H. and Mohd. Noor, Norliza (2020) Automatic framework for the detection of coronary artery calcification in IVUS images. Test Engineering and Management, 83 . pp. 7984-7992. ISSN 0193-4120 https://testmagzine.biz/index.php/testmagzine/article/view/5103 |
| spellingShingle | T58.6-58.62 Management information systems Mohammad, S. Sofian, H. Mohd. Noor, Norliza Automatic framework for the detection of coronary artery calcification in IVUS images |
| title | Automatic framework for the detection of coronary artery calcification in IVUS images |
| title_full | Automatic framework for the detection of coronary artery calcification in IVUS images |
| title_fullStr | Automatic framework for the detection of coronary artery calcification in IVUS images |
| title_full_unstemmed | Automatic framework for the detection of coronary artery calcification in IVUS images |
| title_short | Automatic framework for the detection of coronary artery calcification in IVUS images |
| title_sort | automatic framework for the detection of coronary artery calcification in ivus images |
| topic | T58.6-58.62 Management information systems |
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