IMAGE FEATURE ANALYSIS AND COMPUTER-AIDED DIAGNOSIS IN DIGITAL RADIOGRAPHY .1. AUTOMATED DETECTION OF MICROCALCIFICATIONS IN MAMMOGRAPHY
IMAGE FEATURE ANALYSIS AND COMPUTER-AIDED DIAGNOSIS IN DIGITAL RADIOGRAPHY .1. AUTOMATED DETECTION OF MICROCALCIFICATIONS IN MAMMOGRAPHY
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DOI：
10.1118/1.596065
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发表时间：
1987-07-01
期刊：
影响因子：
3.8
通讯作者：
JOKICH, PM
中科院分区：
文献类型：
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作者：
CHAN, HP;DOI, K;JOKICH, PM
我们已经研究了应用基于计算机的方法来检测数字乳腺X线照片中的微钙化。计算机检测系统是基于一个差异的图像技术，其中的信号抑制图像被从信号增强图像中减去，以消除乳房X线照片中的结构化背景。然后使用适应于微钙化的已知物理特性的信号提取技术来将微钙化与剩余的噪声背景隔离。我们采用蒙特卡罗方法来生成叠加在正常乳腺摄影背景上的模拟微钙化簇。这允许定量评估计算机方法的检测精度以及该精度对微钙化的物理特性的依赖性。我们目前的计算机方法可以实现一个真正的积极集群检测率约为80%，在一个集群每图像的假阳性检测率。这种计算机辅助系统在乳房X光检查解释中的潜在应用通过其检测临床乳房X光检查中微钙化的能力得到了证明。
We have investigated the application of computer-based methods to the detection of microcalcifications in digital mammograms. The computer detection system is based on a difference-image technique in which a signal-suppressed image is subtracted from a signal-enhanced image to remove the structured background in a mammogram. Signal-extraction techniques adapted to the known physical characteristics of microcalcifications are then used to isolate microcalcifications from the remaining noise background. We employ Monte Carlo methods to generate simulated clusters of microcalcifications that are superimposed on normal mammographic backgrounds. This allows quantitative evaluation of detection accuracy of the computer method and the dependence of this accuracy on the physical characteristics of the microcalcifications. Our present computer method can achieve a true-positive cluster detection rate of approximately 80% at a false-positive detection rate of one cluster per image. The potential application of such a computer-aided system to mammographic interpretation is demonstrated by its ability to detect microcalcifications in clinical mammograms.