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The Lung Image Database Consortium (LIDC):A comparison of different size metrics for pulmonary nodule measurements

机译:肺部图像数据库联盟(LIDC):肺结节测量的不同尺寸指标的比较

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摘要

Rationale and ObjectivesTo investigate the effects of choosing between different metrics in estimating the size of pulmonary nodules as a factor both of nodule characterization and of performance of computer aided detection systems, since the latters are always qualified with respect to a given size range of nodules.Materials and MethodsThis study used 265 whole-lung CT scans documented by the Lung Image Database Consortium using their protocol for nodule evaluation. Each inspected lesion was reviewed independently by four experienced radiologists who provided boundary markings for nodules larger than 3 mm. Four size metrics, based on the boundary markings, were considered: a uni-dimensional and two bi-dimensional measures on a single image slice and a volumetric measurement based on all the image slices. The radiologist boundaries were processed and those with four markings were analyzed to characterize the inter-radiologist variation, while those with at least one marking were used to examine the difference between the metrics.ResultsThe processing of the annotations found 127 nodules marked by all of the four radiologists and an extended set of 518 nodules each having at least one observation with three-dimensional sizes ranging from 2.03 to 29.4 mm (average 7.05 mm, median 5.71 mm). A very high inter-observer variation was observed for all these metrics: 95% of estimated standard deviations were in the following ranges [0.49, 1.25], [0.67, 2.55], [0.78, 2.11], and [0.96, 2.69] for the three-dimensional, the uni-dimensional, and the two bi-dimensional size metrics respectively (in mm). Also a very large difference among the metrics was observed: 0.95 probability-coverage region widths for the volume estimation conditional on uni-dimensional, and the two bi-dimensional size measurements of 10mm were 7.32, 7.72, and 6.29 mm respectively.ConclusionsThe selection of data subsets for performance evaluation is highly impacted by the size metric choice. The LIDC plans to include a single size measure for each nodule in its database. This metric is not intended as a gold standard for nodule size; rather, it is intended to facilitate the selection of unique repeatable size limited nodule subsets.
机译:原理和目的为了评估结核结节的大小和计算机辅助检测系统的性能,研究在不同指标之间进行选择对评估肺结节大小的影响,因为后者始终在给定的结节大小范围内合格。材料和方法本研究使用了由肺图像数据库协会记录的265条全肺CT扫描,并使用其协议进行了结节评估。每位受检查的病灶均由四位经验丰富的放射科医生进行独立审查,他们为3 mm以上的结节提供了边界标记。考虑了基于边界标记的四个大小度量:在单个图像切片上的一维和两个二维度量,以及在所有图像切片上的体积度量。处理放射线师的边界,分析带有四个标记的边界以表征放射线间的差异,同时使用具有至少一个标记的边界检查指标之间的差异。结果对注释的处理发现了127个结节,所有结节均被标记四名放射科医生和一组518个结节的扩展集,每个结节至少具有一个观测值,其三维尺寸范围为2.03至29.4毫米(平均7.05毫米,中值5.71毫米)。对于所有这些指标,观察者之间的变化都非常大:95%的估计标准差在以下范围内:[0.49,1.25],[0.67,2.55],[0.78,2.11]和[0.96,2.69]三维尺寸指标,一维尺寸指标和两个二维尺寸指标(以mm为单位)。在指标之间也观察到非常大的差异:以一维为条件的体积估计的0.95概率覆盖区域宽度,两个10mm的二维尺寸分别为7.32、7.72和6.29 mm。性能评估的数据子集受到大小度量选择的极大影响。 LIDC计划为其数据库中的每个结节包括一个单一大小的度量。此度量标准不打算作为结核大小的金标准;相反,其旨在促进对唯一的可重复大小限制的结节子集的选择。

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