Development of the next generation CAD system for mammography

从ROC曲线下面积的角度来看，计算机辅助诊断系统的性能有了很大的提高。主要研究结果如下：1)粗钙化会导致虚假的微钙化检测。他们的检测系统已经被开发出来，用于消除粗钙化引起的微小钙化的假检测。改进后的微钙化点检测系统的性能有了很大的提高。2)提出了一种区分真假微钙化点的方法。它使用从原始乳房X光片的小波变换中获得的特征。与传统系统相比，新系统的假阳性检测率约为1/3。3)进行了大规模的实验，以寻找区分真假肿瘤的半最优特征集。从ROC曲线下区域的角度对490多个特征进行了检查。其中，50个特征被选为半优特征集。采用半最优特征集的肿瘤检测系统性能优良。事实证明，它在减少误报方面是有效的。新系统的假阳性检测率仅为传统系统的一半

The performance of the computer aided diagnosis system for mammography has been greatly improved from the view points of the area under the ROC curve. The primary results are as follows.1) Coarse calcifications can cause false microcalcification detections. Theirs detection system has been developed, which is used to eliminate false microcalcification detections caused by coarse calcifications. The performance of the revised microcalcification detection system has been greatly improved.2) A method for discriminating between true and false microcalcifications has been developed. It uses features obtained from the Wavelet transform of original mammograms. The false positive detection rate of the new system is about one third as compared with the conventional system.3) A large scale experiments to investigate a semi-optimal feature set for discriminating between true and false tumors have been performed. More than 490 features have been examined from the view point of the area under the ROC curve. Among them, 50 features have been selected as a semi-optimal feature set. The performance of the tumor detection system adopting the semi-optimal feature set is excellent. It has been proven to be effective in decreasing false positive detections. The false positive detection rate of the new system is as low as a half of the conventional system