Detection of Atherosclerotic Plaque from Optical Coherence Tomography Images Using Texture-Based Segmentation
| Autor: | Mark Hewko, Sherif S. Sherif, Ammu Prakash, Michael G. Sowa |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
genetic structures
Computer science interferometer swept source optical coherence tomography atherosclerotic plaque Texture (geology) binary image General Biochemistry Genetics and Molecular Biology texture segmentation Watanabe heritable hyperlipidemic rabbit Optical coherence tomography image analysis medicine image quality Segmentation automatic thresholding technique image clustering algorithm vascular tissue optical coherence tomography medicine.diagnostic_test business.industry Pattern recognition spatial gray level dependent matrix method General Medicine eye diseases image processing spatial dependence matrix sense organs Artificial intelligence histogram Unsupervised clustering business |
| Zdroj: | Sovremennye tehnologii v medicine. 7:21-28 |
| ISSN: | 2076-4243 |
| DOI: | 10.17691/stm2015.7.1.03 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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