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首页> 外文期刊>Journal of innovative optical health sciences >3D automatic segmentation method for retinal optical coherence tomography volume data using boundary surface enhancement
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3D automatic segmentation method for retinal optical coherence tomography volume data using boundary surface enhancement

机译:利用边界表面增强的视网膜光学相干断层扫描体数据的3D自动分割方法

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摘要

With the introduction of spectral-domain optical coherence tomography (SD-OCT), much larger image datasets are routinely acquired compared to what was possible using the previous generation of time-domain OCT.?Thus, there is a critical need for the development of three-dimensional (3D) segmentation methods for processing these data. We present here a novel 3D automatic segmentation method for retinal OCT volume data. Briefly, to segment a boundary surface, two OCT volume datasets are obtained by using a 3D smoothing filter and a 3D differential filter. Their linear combination is then calculated to generate new volume data with an enhanced boundary surface, where pixel intensity, boundary position information, and intensity changes on both sides of the boundary surface are used simultaneously. Next, preliminary discrete boundary points are detected from the A-Scans of the volume data. Finally, surface smoothness constraints and a dynamic threshold are applied to obtain a smoothed boundary surface by corre...
机译:与上一代时域OCT相比,光谱域光学相干断层扫描(SD-OCT)的引入可以常规地获取更大的图像数据集。因此,迫切需要开发三维(3D)分割方法来处理这些数据。我们在这里提出一种新颖的3D视网膜OCT体积数据自动分割方法。简而言之,为了分割边界表面,使用3D平滑滤波器和3D差分滤波器获得了两个OCT体积数据集。然后计算它们的线性组合以生成具有增强边界表面的新体数据,其中同时使用像素强度,边界位置信息和边界两侧的强度变化。接下来,从体数据的A扫描中检测出初步的离散边界点。最后,应用表面光滑度约束和动态阈值,通过校正获得光滑的边界表面。

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