| DOI | Resolve DOI: https://doi.org/10.17691/stm2015.7.1.03 |
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| Author | Search for: Prakash, Ammu; Search for: Hewko, Mark D.1; Search for: Sowa, Michael1; Search for: Sherif, Sherif S. |
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| Name affiliation | - National Research Council of Canada. Medical Devices
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| Format | Text, Article |
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| Subject | atherosclerotic plaque; automatic thresholding technique; binary image; histogram; image analysis; image clustering algorithm; image processing; image quality; interferometer; optical coherence tomography; spatial dependence matrix; spatial gray level dependent matrix method; swept source optical coherence tomography; texture segmentation; vascular tissue; Watanabe heritable hyperlipidemic rabbit |
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| Abstract | Detection of atherosclerotic plaque from optical coherence tomography (OCT) images by visual inspection is difficult. We developed a texture based segmentation method to identify atherosclerotic plaque automatically from OCT images without any reliance on visual inspection. Our method involves extraction of texture statistical features (spatial gray level dependence matrix method), application of an unsupervised clustering algorithm (K-means) on these features, and mapping of the clustered regions: background, plaque, vascular tissue and an OCT degraded signal region in feature-space, back to the actual image. We verified the validity of our results by visual comparison to photographs of the vascular tissue with atherosclerotic plaque that were used to generate our OCT images. Our method could be potentially used in clinical studies in OCT imaging of atherosclerotic plaque. |
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| Publication date | 2015 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 21275787 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 7ee506bd-dd14-4738-8a0f-b78742c7cd19 |
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| Record created | 2015-07-14 |
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| Record modified | 2020-04-22 |
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