Dual system approach to computer-aided detection of breast masses on mammograms
Dual system approach to computer-aided detection of breast masses on mammograms
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DOI：
10.1118/1.2357838
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发表时间：
2006-11-01
期刊：
影响因子：
3.8
通讯作者：
Ge, Jun
中科院分区：
文献类型：
--
作者：
Wei, Jun;Chan, Heang-Ping;Ge, Jun
在这项研究中，我们的目的是通过使用一种新的双系统方法来提高我们的质量检测系统的性能，该方法将一个用“平均”质量优化的计算机附加检测（CAD）系统与另一个用“细微”质量优化的CAD系统相结合。这两个单一的CAD系统具有相似的图像处理步骤，包括预筛选，目标分割，形态和纹理特征提取，以及通过基于规则和线性判别分析（LDA）分类器减少误报（FP）。训练一个前馈反向传播人工神经网络来合并两个单一CAD系统中LDA分类器的分数，并区分真实肿块和正常组织。对于未知的测试乳房x光片，两个单独的CAD系统并行应用于图像以检测可疑物体。总共使用了三个数据集来训练和测试系统。从115名患者中收集了230张当前乳房x光片的第一组数据，称为平均质量集。我们还收集了264张乳房x光片，被称为细微肿块组，是这些患者在当前检查前一到两年拍摄的。在交叉验证训练和测试方案中，将平均质量集和细微质量集划分为两个独立的数据集。第三个数据集包含65例260张正常乳房x线照片，用于估计测试期间的FP标记率。当在平均质量集上训练的单个CAD系统应用于具有平均质量的测试集时，基于病例的灵敏度分别为90%，85%和80%，每张图像的FP标记率分别为2.2,1.8和1.5。使用双CAD系统，在相同的基于病例的灵敏度下，FP标记率分别降低到每张图像1.2,0.9和0.7。使用平均质量或细微质量的测试集比较双系统和单系统时，自由反应受者工作特征曲线的改善有统计学意义（P < 0.05）。(c) 2006年美国医学物理学家协会。
In this study, our purpose was to improve the performance of our mass detection system by using a new dual system approach which combines a computer-added detection (CAD) system optimized with "average" masses with another CAD system optimized with "subtle" masses. The two single CAD systems have similar image processing steps, which include prescreening, object segmentation, morphological and texture feature extraction, and false positive (FP) reduction by rule-based and linear discriminant analysis (LDA) classifiers. A feed-forward backpropagation artificial neural network was trained to merge the scores from the LDA classifiers in the two single CAD systems and differentiate true masses from normal tissue. For an unknown test mammogram, the two single CAD systems are applied to the image in parallel to detect suspicious objects. A total of three data sets were used for training and testing the systems. The first data set of 230 current mammograms, referred to as the average mass set, was collected from 115 patients. We also collected 264 mammograms, referred to as the subtle mass set, which were one to two years prior to the current exam from these patients. Both the average and the subtle mass sets were partitioned into two independent data sets in a cross validation training and testing scheme. A third data set containing 65 cases with 260 normal mammograms was used to estimate the FP marker rates during testing. When the single CAD system trained on the average mass set was applied to the test set with average masses, the FP marker rates were 2.2, 1.8, and 1.5 per image at the case-based sensitivities of 90%, 85%, and 80%, respectively. With the dual CAD system, the FP marker rates were reduced to 1.2, 0.9, and 0.7 per image, respectively, at the same case-based sensitivities. Statistically significant (P < 0.05) improvements on the free response receiver operating characteristic curves were observed when the dual system and the single system were compared using the test sets with either average masses or subtle masses. (c) 2006 American Association of Physicists in Medicine.