Kiss Gabriel, Van Cleynenbreugel Johan, Thomeer Maarten, Suetens Paul, Marchal Guy
Department of Medicine, Medical Image Computing (Radiology--ESAT/PSI), University Hospital Gasthuisberg, Herestraat 49, 3000 Leuven, Belgium,
Eur Radiol. 2002 Jan;12(1):77-81. doi: 10.1007/s003300101040. Epub 2001 Jul 12.
The success of CT colonography (CTC) depends on appropriate tools for quick and accurate diagnostic reading. Current advancements in computer technology have the potential to bring such tools even to personal computer level. In this paper a technique for computed-aided diagnosis (CAD) using CT colonography is described. The method uses a combination of surface normal and sphere fitting methods to label positions in the volume data, which have a strong likelihood of being polyps, and presents them in a user-friendly way. The method was tested on a study group of 18 patients and the detection rate for polyps of 10 mm or larger was 100%, comparable to that of human readers. The price paid for a high detection rate was a large number of approximately eight false-positive findings per case. Our results show that CAD is feasible, and if the number of false positives is further reduced, then this method can be useful for clinical screenings.
CT结肠成像（CTC）的成功取决于用于快速准确诊断性阅片的合适工具。计算机技术的当前进展有可能将此类工具甚至带到个人电脑层面。本文描述了一种使用CT结肠成像的计算机辅助诊断（CAD）技术。该方法结合了表面法线和球体拟合方法来标记体积数据中极有可能是息肉的位置，并以用户友好的方式呈现这些位置。该方法在一组18名患者的研究队列中进行了测试，10毫米及以上息肉的检测率为100%，与人类阅片者相当。为高检测率付出的代价是每例大约有8个假阳性结果。我们的结果表明CAD是可行的，如果假阳性数量进一步减少，那么该方法可用于临床筛查。
