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An observer study comparing spot imaging regions selected by radiologists and a computer for an automated stereo spot mammography technique.

机译:一项观察员研究比较了放射科医生和计算机选择的用于自动立体乳房X线照相技术的点成像区域。

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We are developing an automated stereo spot mammography technique for improved imaging of suspicious dense regions within digital mammograms. The technique entails the acquisition of a full-field digital mammogram, automated detection of a suspicious dense region within that mammogram by a computer aided detection (CAD) program, and acquisition of a stereo pair of images with automated collimation to the suspicious region. The latter stereo spot image is obtained within seconds of the original full-field mammogram, without releasing the compression paddle. The spot image is viewed on a stereo video display. A critical element of this technique is the automated detection of suspicious regions for spot imaging. We performed an observer study to compare the suspicious regions selected by radiologists with those selected by a CAD program developed at the University of Michigan. True regions of interest (TROIs) were separately determined by one of the radiologists who reviewed the original mammograms, biopsyimages, and histology results. We compared the radiologist and computer-selected regions of interest (ROIs) to the TROIs. Both the radiologists and the computer were allowed to select up to 3 regions in each of 200 images (mixture of 100 CC and 100 MLO views). We computed overlap indices (the overlap index is defined as the ratio of the area of intersection to the area of interest) to quantify the agreement between the selected regions in each image. The averages of the largest overlap indices per image for the 5 radiologist-to-computer comparisons were directly related to the average number of regions per image traced by the radiologists (about 50% for 1 region/image, 84% for 2 regions/image and 96% for 3 regions/image). The average of the overlap indices with all of the TROIs was 73% for CAD and 76.8% +/- 10.0% for the radiologists. This study indicates that the CAD determined ROIs could potentially be useful for a screening technique that includes stereo spot mammography imaging.
机译:我们正在开发一种自动立体乳腺X线摄影技术,以改善数字乳腺X线照片中可疑密集区域的成像。该技术需要获取全场数字乳房X线照片,通过计算机辅助检测(CAD)程序自动检测该乳房X线照片中的可疑密集区域,以及获取具有自动准直到可疑区域的立体图像对。后者的立体点图像是在原始全场乳房X线照片的几秒钟内获得的,而无需释放压缩板。在立体视频显示器上查看专色图像。该技术的关键要素是自动检测可疑区域以进行斑点成像。我们进行了一项观察员研究,比较了放射科医生选择的可疑区域和密歇根大学开发的CAD程序选择的可疑区域。真正的受关注区域(TROIs)由一位放射科医生单独确定,他们检查了原始的乳房X线照片,活检图像和组织学结果。我们将放射科医生和计算机选择的感兴趣区域(ROI)与TROI进行了比较。放射科医生和计算机都可以在200张图像(100 CC和100 MLO视图的混合)中选择最多3个区域。我们计算了重叠指数(重叠指数定义为相交面积与感兴趣区域的比率),以量化每个图像中选定区域之间的一致性。 5次放射科医生与计算机的比较中,每幅图像最大重叠指数的平均值与放射科医生追踪的每幅图像的平均区域数量直接相关(1个区域/每个图像约占50%,2个区域/每个图像约占84% 3个区域/图片占96%)。对于所有TROI,CAD的重叠指数平均值为73%,放射科医师为76.8%+/- 10.0%。这项研究表明,CAD确定的ROI可能对包括立体乳房X线照相成像的筛查技术有用。

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