EFFECT OF CASE SELECTION ON THE PERFORMANCE OF COMPUTER-AIDED DETECTION SCHEMES
EFFECT OF CASE SELECTION ON THE PERFORMANCE OF COMPUTER-AIDED DETECTION SCHEMES
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DOI：
10.1118/1.597287
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发表时间：
1994-02-01
期刊：
影响因子：
3.8
通讯作者：
SCHMIDT, RA
中科院分区：
文献类型：
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作者：
NISHIKAWA, RM;GIGER, ML;SCHMIDT, RA
用于训练和测试计算机辅助诊断（CAD）方案的临床病例的选择可以影响测试结果（即，错误率）。在这项研究中，我们故意修改了我们的测试数据库的组件，以研究这种修改对测量性能的影响。使用计算机化的计划，从乳房X线照片的乳房肿块的自动检测，它被发现，该计划的灵敏度范围在26%和100%之间（在一个假阳性率为1.0每图像），这取决于用于测试该计划的情况。即使构成数据库的病例中有20%的变化，也会使测量的灵敏度降低15%-25%。由于测得的性能对测试数据库的依赖性很强，因此很难可靠地估计CAD方案的精度。此外，当使用不同的情况进行测试时，比较不同的CAD方案是有问题的。共享数据库，创建一个共同的数据库，或使用定量措施来表征数据库是这个问题的可能解决方案。然而，这些解决方案目前都不存在或没有得到实践。因此，作为短期解决方案，建议在提供性能数据时报告用于选择病例的方法以及相关图像特征的直方图或平均值和标准差。
The choice of clinical cases used to train and test a computer-aided diagnosis (CAD) scheme can affect the test results (i.e., error rate). In this study, we deliberately modified the components of our testing database to study the effects of this modification on measured performance. Using a computerized scheme for the automated detection of breast masses from mammograms, it was found that the sensitivity of the scheme ranged between 26% and 100% (at a false positive rate of 1.0 per image) depending on the cases used to test the scheme. Even a 20% change in the cases comprising the database can reduce the measured sensitivity by 15%-25%. Because of the strong dependence of measured performance on the testing database, it is difficult to estimate reliably the accuracy of a CAD scheme. Furthermore, it is questionable to compare different CAD schemes when different cases are used for testing. Sharing databases, creating a common database, or using a quantitative measure to characterize databases are possible solutions to this problem. However, none of these solutions exists or is practiced at present. Therefore, as a short-term solution, it is recommended that the method used for selecting cases, and histograms or mean and standard deviations of relevant image features be reported whenever performance data are presented.