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Method for local surface smoothing with application to chest wall nodule segmentation in lung CT data

机译:用于肺CT数据中胸壁结节分割的局部表面平滑方法

摘要

We present an algorithm for local surface smoothing in a defined Volume of Interest (“VOI”) cropped from three-dimensional (“3D”) volume data, such as lung computer tomography (“CT”) data. Because the VOI is generally a smooth and piecewise linear surface, the inclusion of one or more bumps may suggest an abnormality. In lung CT data, for example, such bumps can be nodules that are grown from the chest wall. The nodules may represent a possibility of lung cancer. Through surface smoothing, potential pathologies are separated from the surrounding anatomical structures. For example, nodules may be segmented from the chest wall. The separated pathologies can be analyzed as diagnostic evidence.
机译:我们提出了一种用于从三维(“ 3D”)体积数据(例如肺部计算机断层扫描(CT))数据中裁剪的定义的“感兴趣的体积”(VOI)中进行局部表面平滑的算法。由于VOI通常是光滑且分段的线性表面,因此包含一个或多个凸块可能表明存在异常。例如,在肺部CT数据中,此类肿块可能是从胸壁长出的结节。结节可能代表了肺癌的可能性。通过表面平滑处理,可将潜在的病理学与周围的解剖结构分开。例如,结节可从胸壁切开。分离的病理可以作为诊断证据进行分析。

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