Kegelmeyer W P, Pruneda J M, Bourland P D, Hillis A, Riggs M W, Nipper M L
Sandia National Laboratories, Livermore, Calif.
Radiology. 1994 May;191(2):331-7. doi: 10.1148/radiology.191.2.8153302.
To study the use of a computer vision method as a second reader for the detection of spiculated lesions on screening mammograms.
An algorithmic computer process for the detection of spiculated lesions on digitized screen-film mammograms was applied to 85 four-view clinical cases: 36 cases with cancer proved by means of biopsy and 49 cases with negative findings at examination and follow-up. The computer detections were printed as film with added outlines that indicated the suspected cancers. Four radiologists screened the 85 cases twice, once without and once with the computer reports as ancillary films.
The algorithm alone achieved 100% sensitivity, with a specificity of 82%. The computer reports increased the average radiologist sensitivity by 9.7% (P = .005), moving from 80.6% to 90.3%, with no decrease in average specificity.
The study demonstrated that computer analysis of mammograms can provide a substantial and statistically significant increase in radiologist screening efficacy.
研究将计算机视觉方法用作二次阅片工具,以检测筛查乳腺钼靶片中的毛刺状病变。
将一种用于检测数字化屏-片乳腺钼靶片中毛刺状病变的算法计算机程序应用于85例四视图临床病例,其中36例经活检证实为癌症,49例检查及随访结果为阴性。计算机检测结果打印在胶片上,并添加轮廓以指示疑似癌症。四位放射科医生对这85例病例进行了两次筛查,一次不参考计算机报告,一次将计算机报告作为辅助胶片参考。
该算法单独使用时灵敏度达到100%,特异性为82%。计算机报告使放射科医生的平均灵敏度提高了9.7%(P = .005),从80.6%提高到90.3%,平均特异性没有降低。
该研究表明,乳腺钼靶片的计算机分析可以显著提高放射科医生的筛查效率,且具有统计学意义。