Matsumoto T, Yoshimura H, Giger M L, Doi K, MacMahon H, Montner S M, Nakanishi T
Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, University of Chicago, Illinois 60637.
Invest Radiol. 1992 Jun;27(6):471-5. doi: 10.1097/00004424-199206000-00013.
To alert radiologists to possible nodule locations and subsequently to reduce the number of false-negative diagnoses, the authors are developing a computer-aided diagnostic (CAD) scheme for the detection of lung nodules in digital chest images.
A computer-vision scheme was applied to photofluorographic films obtained in a mass survey for detection of asymptomatic lung cancer in Japan. Ninety-five patients with abnormal test results who had primary and metastatic lung cancers and 103 patients with normal test results were included.
The sensitivity of the computer output was comparable with that of physicians in this mass survey (62%). The computer detected approximately 40% of all nodules missed in the mass survey, but missed 17 true-positive results identified in the mass survey. The CAD scheme produced an average of 15 false-positive findings per image.
If the number of false-positive results can be significantly reduced, computer-vision schemes such as this may have a role in lung cancer screening programs.
为提醒放射科医生注意可能存在结节的位置,进而减少假阴性诊断的数量,作者正在开发一种用于在数字化胸部图像中检测肺结节的计算机辅助诊断(CAD)方案。
将一种计算机视觉方案应用于在日本进行的无症状肺癌大规模筛查中获得的荧光摄影胶片。纳入了95例检测结果异常且患有原发性和转移性肺癌的患者以及103例检测结果正常的患者。
在这次大规模筛查中,计算机输出的敏感性与医生的相当(62%)。计算机检测出了大规模筛查中遗漏的所有结节中的约40%,但也遗漏了大规模筛查中确定的17个真阳性结果。CAD方案每张图像平均产生15个假阳性结果。
如果能显著减少假阳性结果的数量,像这样的计算机视觉方案可能在肺癌筛查项目中发挥作用。