A new ROC analysis method considering the correlation between neighboring pixels.
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.
Medical Imaging Research Center, Illinois Institute of Technology, Chicago, IL, USA.
Xin
X
Liu
Imam Samil
IS
Yetik
D000465:Algorithms; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013223:Statistics as Topic