Chan H P, Doi K, Galhotra S, Vyborny C J, MacMahon H, Jokich P M
Med Phys. 1987 Jul-Aug;14(4):538-48. doi: 10.1118/1.596065.
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.
我们已经研究了基于计算机的方法在数字乳腺钼靶片中微钙化检测方面的应用。该计算机检测系统基于一种差分图像技术，即从信号增强图像中减去信号抑制图像，以去除乳腺钼靶片中的结构化背景。然后，采用适应微钙化已知物理特性的信号提取技术，将微钙化从剩余的噪声背景中分离出来。我们使用蒙特卡罗方法生成模拟的微钙化簇，并将其叠加在正常的乳腺钼靶背景上。这使得能够对计算机方法的检测准确性以及该准确性对微钙化物理特性的依赖性进行定量评估。我们目前的计算机方法在每张图像假阳性检测率为一个簇的情况下，能够实现约80%的真阳性簇检测率。这种计算机辅助系统在乳腺钼靶解读中的潜在应用通过其在临床乳腺钼靶片中检测微钙化的能力得到了证明。
