Computer-assisted detection of mammographic masses: A template matching scheme based on mutual information
Computer-assisted detection of mammographic masses: A template matching scheme based on mutual information
复制标题
DOI：
10.1118/1.1589494
复制
发表时间：
2003-08-01
期刊：
影响因子：
3.8
通讯作者：
Floyd, CE
中科院分区：
文献类型：
--
作者：
Tourassi, GD;Vargas-Voracek, R;Floyd, CE
本研究的目的是开发一种基于知识的方案，用于在数字化筛查乳房x光片上检测肿块。计算机辅助检测（CAD）方案利用具有已知基础真理的乳房x线摄影感兴趣区域（roi）的知识数据库。数据库中的每个ROI都充当模板。CAD系统遵循模板匹配方法，以互信息作为相似性度量来确定查询乳房x线照相术ROI是否描绘了真实的肿块。根据其信息内容，检索数据库中所有相似的roi并对其进行排序。然后，根据查询的最佳匹配计算决策索引。决策指数有效地将最匹配模板的相似性指数和基本真值结合到关于查询乳房x线照相术ROI中肿块存在的预测中。该系统的开发和评估使用了从乳腺筛查数字数据库中提取的1465个roi数据库。经证实的roi 809例（恶性455例，良性354例），正常roi 656例。使用留一抽样方案和接收机工作特性分析来评估CAD性能。根据决策指标的制定，CAD性能最高可达A(z) = 0.87 +/- 0.01。恶性肿块和良性肿块的CAD检出率一致。此外，还详细研究了某些实现参数对所提出CAD方案的检测精度和速度的影响。(C) 2003年美国医学物理学家协会。
The purpose of this study was to develop a knowledge-based scheme for the detection of masses on digitized screening mammograms. The computer-assisted detection (CAD) scheme utilizes a knowledge databank of mammographic regions of interest (ROIs) with known ground truth. Each ROI in the databank serves as a template. The CAD system follows a template matching approach with mutual information as the similarity metric to determine if a query mammographic ROI depicts a true mass. Based on their information content, all similar ROIs in the databank are retrieved and rank-ordered. Then, a decision index is calculated based on the query's best matches. The decision index effectively combines the similarity indices and ground truth of the best-matched templates into a prediction regarding the presence of a mass in the query mammographic ROI. The system was developed and evaluated using a database of 1465 ROIs extracted from the Digital Database for Screening Mammography. There were 809 ROIs with confirmed masses (455 malignant and 354 benign) and 656 normal ROIs. CAD performance was assessed using a leave-one-out sampling scheme and Receiver Operating Characteristics analysis. Depending on the formulation of the decision index, CAD performance as high as A(z) = 0.87 +/- 0.01 was achieved. The CAD detection rate was consistent for both malignant and benign masses. In addition, the impact of certain implementation parameters on the detection accuracy and speed of the proposed CAD scheme was studied in more detail. (C) 2003 American Association of Physicists in Medicine.