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CT colonography with computer-aided detection: automated recognition of ileocecal valve to reduce number of false-positive detections.

机译:带计算机辅助检测的CT结肠造影:自动识别回盲瓣,以减少假阳性检测的次数。

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摘要

The ileocecal valve (ICV) is a common cause of false-positive detections of polyps at computed tomographic (CT) colonography with computer-aided detection (CAD). The authors developed a CAD algorithm for differentiating the ICV from a true polyp and evaluated this algorithm by using two colonoscopy-confirmed CT colonography data sets. Data sets 1 and 2 consisted of the data obtained at CT colonographic examinations performed in 20 and 40 patients, respectively. Forty of these patients had at least one polyp 1 cm or larger. For data set 1, the proposed ICV recognition algorithm eliminated three of nine (33%; 95% confidence interval [CI]: 8%, 70%) false-positive CAD detections that were attributable to the ICV and none of the true-positive polyp detections. For data set 2, with use of identical parameters, the algorithm eliminated 11 of 18 (61%; 95% CI: 36%, 83%) false-positive detections that were attributable to the ICV and none of the true-positive detections. The thresholds used to recognize the ICV were a mean internal CT attenuation of less than -124 HU and a volume of greater than 1.5 cm(3). The proposed algorithm successfully recognized the ICV and eliminated it in some cases. This result is clinically important because, by reducing the frequency of a common cause of false-positive detections, this algorithm may improve the efficiency of physicians who use CAD.
机译:回盲瓣(ICV)是计算机断层扫描(CT)结肠造影和计算机辅助检测(CAD)时对息肉假阳性检测的常见原因。作者开发了一种将ICV与真正的息肉区分开的CAD算法,并使用两个经结肠镜检查确认的CT结肠造影数据集对该算法进行了评估。数据集1和2由分别在20位和40位患者中进行的CT结肠造影检查获得的数据组成。这些患者中有40位至少有1 cm或更大的息肉。对于数据集1,提出的ICV识别算法消除了9种错误中的3种(33%; 95%置信区间[CI]:8%,70%),这些假阳性CAD检测归因于ICV,而没有一个是真阳性息肉检测。对于数据集2,使用相同的参数,该算法消除了18个错误中的11个(61%; 95%CI:36%,83%),这些错误与ICV相关,而没有一个是真正的阳性。用于识别ICV的阈值是平均内部CT衰减小于-124 HU,体积大于1.5 cm(3)。所提出的算法成功地识别了ICV,并在某些情况下将其消除。该结果在临床上很重要,因为通过减少导致假阳性检测的常见原因的频率,此算法可以提高使用CAD的医师的效率。

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