We propose a method for the automated in vivo thickness measurement of the human eardrum in OCT imaging. The method is based on extraction curvilinear structures using eigenvectors and eigenvalues of smoothing image Hessian (Steger method). This allows for extracting the central line of the eardrum and calculating the normal to each point. The latter circumstance makes it possible to find the proper thickness of an arbitrarily oriented eardrum having a complex shape. The algorithm works correctly despite the presence of other image elements complicating the central line and borders extraction process (presence of an effusion or structures with bright borders—bones). The algorithm does not require large computing power and can be applied to real time image processing. In addition, a comparison of the effectiveness of the proposed method with a Canny edge detector is given.

中文翻译：

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OCT图像处理中用于自动鼓膜厚度测量的微分几何方法

我们提出了一种在OCT成像中自动测定人耳膜的体内厚度的方法。该方法基于使用平滑图像Hessian的特征向量和特征值提取曲线结构（Steger方法）。这样可以提取鼓膜的中心线并计算每个点的法线。在后一种情况下，可以找到形状复杂的任意取向的鼓膜的适当厚度。尽管存在其他使中心线和边界提取过程复杂化的图像元素（存在渗出物或边界较明亮的结构（骨骼）），该算法仍能正常工作。该算法不需要很大的计算能力，可以应用于实时图像处理。此外，