Rezaei, Z. and Selamat, A. and Taki, A. and Mohd. Rahim, M. S. and Abdul Kadir, M. R. (2015) Detection of vulnerable plaque in virtual histology intravascular ultrasound images using SVM. Frontiers in Artificial Intelligence and Applications, 276 . pp. 149-156. ISSN 0922-6389
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Official URL: https://doi.org/10.3233/978-1-61499-522-7-149
Abstract
Virtual Histology Intravascular Ultrasound (VH-IVUS) is a clinically available for visualizing color coded of coronary artery plaque. However, current VH-IVUS image processing techniques have not considered the combinations of features to identify vulnerable plaque. This paper presents a new method for classification of TCFA (thin-cap fibroatheromas) and Non-TCFA plaque based on combined features using the VH-IVUS images using support vector machine (SVM). The proposed method is applied to 546 in-vivo VH-IVUS images. Results proved the dominance of our proposed method with accuracy rates of 98.15% for TCFA.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | feature extraction, segmentation, textural feature |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Computing |
| ID Code: | 59219 |
| Deposited By: | Haliza Zainal |
| Deposited On: | 18 Jan 2017 01:50 |
| Last Modified: | 26 Jan 2022 02:49 |
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