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Texture based segmentation method to detect atherosclerotic plaque from optical tomography images

机译:基于纹理的分割方法从光学断层扫描图像中检测动脉粥样硬化斑块

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Optical coherence tomography (OCT) imaging has been widely employed in assessing cardiovascular disease. Atherosclerosis is one of the major cause cardio vascular diseases. However visual detection of atherosclerotic plaque from OCT images is often limited and further complicated by high frame rates. We developed a texture based segmentation method to automatically detect plaque and non plaque regions from OCT images. To verify our results we compared them to photographs of the vascular tissue with atherosclerotic plaque that we used to generate the OCT images. Our results show a close match with photographs of vascular tissue with atherosclerotic plaque. Our texture based segmentation method for plaque detection could be potentially used in clinical cardiovascular OCT imaging for plaque detection.
机译:光学相干断层扫描(OCT)成像已广泛用于评估心血管疾病。动脉粥样硬化是引起心血管疾病的主要原因之一。然而,从OCT图像中对动脉粥样硬化斑块的视觉检测通常受到限制并且由于高帧速率而进一步复杂化。我们开发了一种基于纹理的分割方法,可从OCT图像中自动检测斑块和非斑块区域。为了验证我们的结果,我们将它们与用于生成OCT图像的带有动脉粥样硬化斑块的血管组织照片进行了比较。我们的结果显示与动脉粥样硬化斑块的血管组织照片非常吻合。我们用于斑块检测的基于纹理的分割方法可能会在临床心血管OCT成像中用于斑块检测。

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