Liu Xin, Yetik Imam Samil
Medical Imaging Research Center, Illinois Institute of Technology, Chicago, IL, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:4422-5. doi: 10.1109/EMBC.2012.6346947.
In this paper, we introduce a novel receiver operating characteristic (ROC) analysis method that considers spatial correlation between pixels to evaluate classification algorithms. ROC analysis is one of the most important tools in the evaluation of medical images and computer aided diagnosis (CAD) systems. It provides a comprehensive description of the detection accuracy of the test image. To evaluate the localization performance, operating points of ROC curves are obtained based on the classification results of individual pixels. To this date, the confidence level or intensity value of each pixel is assumed to be independent within the image. However, this assumption is not satisfied in real problems. In this paper, a new ROC analysis algorithm that considers the correlation between neighboring pixels is proposed. Our results show that the new ROC curves provide a more accurate evaluation of the test image.
在本文中，我们介绍了一种新颖的接收器操作特性（ROC）分析方法，该方法考虑像素间的空间相关性以评估分类算法。ROC分析是医学图像和计算机辅助诊断（CAD）系统评估中最重要的工具之一。它全面描述了测试图像的检测准确性。为了评估定位性能，基于各个像素的分类结果获得ROC曲线的操作点。迄今为止，图像中每个像素的置信度水平或强度值被假定为相互独立。然而，这一假设在实际问题中并不成立。本文提出了一种考虑相邻像素间相关性的新ROC分析算法。我们的结果表明，新的ROC曲线能对测试图像提供更准确的评估。
