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首页> 外文期刊>Medical Physics >Correlation of free-response and receiver-operating-characteristic area-under-the-curve estimates: Results from independently conducted FROCROC studies in mammography
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Correlation of free-response and receiver-operating-characteristic area-under-the-curve estimates: Results from independently conducted FROCROC studies in mammography

机译:曲线下估计值的自由响应和接收者操作特征的相关性:乳房X线照片中独立进行的FROCROC研究的结果

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Purpose: From independently conducted free-response receiver operating characteristic (FROC) and receiver operating characteristic (ROC) experiments, to study fixed-reader associations between three estimators: the area under the alternative FROC (AFROC) curve computed from FROC data, the area under the ROC curve computed from FROC highest rating data, and the area under the ROC curve computed from confidence-of-disease ratings. Methods: Two hundred mammograms, 100 of which were abnormal, were processed by two image-processing algorithms and interpreted by four radiologists under the FROC paradigm. From the FROC data, inferred-ROC data were derived, using the highest rating assumption. Eighteen months afterwards, the images were interpreted by the same radiologists under the conventional ROC paradigm; conventional-ROC data (in contrast to inferred-ROC data) were obtained. FROC and ROC (inferred, conventional) data were analyzed using the nonparametric area-under-the-curve (AUC), (AFROC and ROC curve, respectively). Pearson correlation was used to quantify the degree of association between the modality-specific AUC indices and standard errors were computed using the bootstrap-after-bootstrap method. The magnitude of the correlations was assessed by comparison with computed Obuchowski-Rockette fixed reader correlations. Results: Average Pearson correlations (with 95 confidence intervals in square brackets) were: Corr(FROC, inferred ROC) 0.760.64, 0.84 > Corr(inferred ROC, conventional ROC) 0.400.18, 0.58 > Corr (FROC, conventional ROC) 0.320.16, 0.46. Conclusions: Correlation between FROC and inferred-ROC data AUC estimates was high. Correlation between inferred- and conventional-ROC AUC was similar to the correlation between two modalities for a single reader using one estimation method, suggesting that the highest rating assumption might be questionable.
机译:目的:通过独立进行的自由响应接收机工作特性(FROC)和接收机工作特性(ROC)实验,研究三种估算器之间的固定阅读器关联:根据FROC数据计算出的替代FROC曲线下的面积(AFROC),面积根据FROC最高评级数据计算得出的ROC曲线下方的区域,以及根据疾病置信度评级计算得出的ROC曲线下方的区域。方法:用两种图像处理算法处理了200幅乳腺X线照片,其中100幅异常,并由FROC范式下的4名放射线医师进行了解释。从FROC数据中,使用最高评级假设得出推断的ROC数据。 18个月后,相同的放射线医师根据传统的ROC范式对图像进行了解释。获得了常规ROC数据(与推断的ROC数据相反)。使用非参数曲线下面积(AUC)(分别为AFROC和ROC曲线)分析了FROC和ROC(推断的常规数据)数据。皮尔逊相关性用于量化模态特定的AUC指标之间的关联度,标准误差使用引导后引导方法进行计算。通过与计算的Obuchowski-Rockette固定阅读器相关性进行比较来评估相关性的大小。结果:平均皮尔逊相关系数(方括号中有95个置信区间)为:Corr(FROC,推断的ROC)0.760.64,0.84> Corr(推断的ROC,传统的ROC)0.400.18,0.58> Corr(FROC,传统的ROC) 0.320.16、0.46。结论:FROC和推断的ROC数据AUC估计值之间的相关性很高。推论和传统ROC AUC之间的相关性类似于使用一种估计方法的单个读者的两种模式之间的相关性,这表明最高评级的假设可能是有问题的。

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