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A novel Dermo-epidermal localization algorithm for Swept source OCT images of human skin

机译:一种新型Dermo表皮定位算法,用于人体皮肤的扫掠源OCT图像

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Optical coherence tomography (OCT) is a noninvasive diagnostic method that offers a view into the superficial layers of the skin in vivo in real-time. OCT delivers morphological images of microstructures within the skin. Epidermal thickness in OCT images is of paramount importance, since dermo-epidermal junction (DEJ) location alteration is the start of several skin abnormalities. Due to the presence of speckle noise, devising an algorithm for locating DEJ in the OCT images is challenging. In this study we propose a semi-automatic DEJ detection algorithm based on graph theory that is resistant to speckle. In this novel approach we use attenuation map as a complementary feature compared to the previous methods that are mainly based on the intensity information. The method is based on converting border segmentation problem to the shortest path problem using graph theory. To smooth borders, we introduced a thinning fuzzy system enabling closer match to manual segmentation. Subsequently, an averaged A-scan analysis is performed to obtain the mean epidermal thickness. The DEJ detection method is performed on 96 B-Scan OCT skin images taken from different sites of body of healthy individuals. The results are evaluated based on several expert's visual analysis.
机译:光学相干断层扫描(OCT)是一种非侵入性诊断方法,其实时地在体内浅进入皮肤的浅层层。 OCT在皮肤内提供微观结构的形态学图像。由于Dermo-Epidermal结(DEJ)位置改变是几种皮肤异常的开始,所以OCT图像中表皮厚度至关重要。由于存在散斑噪声,设计用于在OCT图像中定位DEJ的算法是具有挑战性的。在这项研究中,我们提出了一种基于抗斑点的图形理论的半自动DEJ检测算法。在这种新方法中,与主要基于强度信息的先前方法相比,我们使用衰减图作为互补特征。该方法基于使用图论将边界分割问题转换为最短路径问题。为了平滑边框,我们介绍了一种更薄的模糊系统,使手动分割更近。随后,进行平均扫描分析以获得平均表皮厚度。 DEJ检测方法在从健康个体的不同部位拍摄的96b扫描OCT皮肤图像上进行。结果基于几个专家的视觉分析评估。

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