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A New Algorithm for Local Surface Smoothing with Application to Chest Wall Nodule Segmentation in Lung CT Data

机译:一种新的局部表面平滑施用肺墙结节分段局部平滑算法

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We present an algorithm for local surface smoothing in a defined Volume of Interest (VOI) cropped from 3D volume data, such as lung CT data. There is generally a smooth and piecewise linear surface in the VOI, with one or more bumps on the surface. In lung CT data, such bumps can be nodules that are grown from the chest wall, which represent a possibility of lung cancer. Through surface smoothing, the nodules are segmented from the chest wall and its size can be measured as diagnostic evidence. The algorithm has the advantage of high consistency and robustness, and is useful in a segmentation module of a Compute Aided Diagnosis (CAD) system.
机译:我们介绍了一种从3D卷数据裁剪的定义体积的兴趣(VOI)中局部表面平滑算法,例如肺CT数据。 VOI中通常存在平滑和分段线性表面,表面上具有一个或多个凸块。在肺CT数据中,这种凸起可以是从胸壁生长的结节,其代表肺癌的可能性。通过表面平滑,结节从胸壁分段,其尺寸可以测量为诊断证据。该算法具有高一致性和稳健性的优点,并且在计算辅助诊断(CAD)系统的分割模块中是有用的。

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