LUNGx Challenge for computerized lung nodule classification
LUNGx Challenge for computerized lung nodule classification
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DOI：
10.1117/1.jmi.3.4.044506
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发表时间：
2016-10-01
影响因子：
2.4
通讯作者：
Clarke, Laurence P.
中科院分区：
文献类型：
--
作者：
Armato, Samuel G., III;Drukker, Karen;Clarke, Laurence P.
这项工作的目的是描述诊断计算机断层扫描（CT）扫描的肺结节的计算机化分类为良性或恶性的LUNGx挑战，并报告参与者的计算机化方法的性能沿着参加观察者研究的六名放射科医生在同一数据集上执行相同的挑战任务。该挑战提供了一套校准和测试扫描，建立了一个性能评估过程，并为案例传播和结果提交创建了一个基础设施。10个组对73个肺结节（37个良性和36个恶性）应用他们自己的方法，这些肺结节被选择来实现两个队列之间的近似大小匹配。这些方法的受试者工作特征曲线下面积（AUC）值范围为0.50至0.68;只有三种方法在统计学上优于随机猜测。放射科医生的AUC值范围为0.70至0.85;三名放射科医生的表现在统计学上优于表现最好的计算机方法。LUNGx Challenge比较了计算机化方法在CT扫描上区分良性和恶性肺结节的任务中的性能，并将其置于放射科医生执行相同任务的背景下。挑战案例的持续公开提供将为医学成像研究界提供宝贵的资源。(C)2016年，美国光电仪器工程师学会（SPIE）
The purpose of this work is to describe the LUNGx Challenge for the computerized classification of lung nodules on diagnostic computed tomography (CT) scans as benign or malignant and report the performance of participants' computerized methods along with that of six radiologists who participated in an observer study performing the same Challenge task on the same dataset. The Challenge provided sets of calibration and testing scans, established a performance assessment process, and created an infrastructure for case dissemination and result submission. Ten groups applied their own methods to 73 lung nodules (37 benign and 36 malignant) that were selected to achieve approximate size matching between the two cohorts. Area under the receiver operating characteristic curve (AUC) values for these methods ranged from 0.50 to 0.68; only three methods performed statistically better than random guessing. The radiologists' AUC values ranged from 0.70 to 0.85; three radiologists performed statistically better than the best-performing computer method. The LUNGx Challenge compared the performance of computerized methods in the task of differentiating benign from malignant lung nodules on CT scans, placed in the context of the performance of radiologists on the same task. The continued public availability of the Challenge cases will provide a valuable resource for the medical imaging research community. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)