Computerized detection of colorectal masses in CT colonography based on fuzzy merging and wall-thickening analysis
Computerized detection of colorectal masses in CT colonography based on fuzzy merging and wall-thickening analysis
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DOI：
10.1118/1.1668591
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发表时间：
2004-04-01
期刊：
影响因子：
3.8
通讯作者：
Yoshida, H
中科院分区：
文献类型：
--
作者：
Näppi, JJ;Frimmel, H;Yoshida, H
近年来，已经开发了几种计算机辅助检测（CAD）方案用于CT结肠造影（CTC）中息肉的检测。然而，很少有研究已经解决的问题，计算机检测结直肠肿块的CTC。这主要是因为肿块的大小和侵入性被放射科医生认为是很好的可视化。尽管如此，自动检测肿块将自然补充CTC中自动检测息肉，并将为放射科医生提供更全面的计算机辅助。因此，在这项研究中，我们确定了一些与计算机检测群众的问题，我们开发了一个方案，可以集成到一个CAD方案检测息肉的群众的计算机检测。质量检测方案的性能通过应用于临床CTC数据集进行评价。82例患者在仰卧位和俯卧位进行螺旋CT扫描，重建间隔为1.0-5.0 mm。14名患者（17%）共有14个30-50 mm的肿块，16名患者（20%）共有30个直径5-25 mm的息肉。4例患者同时存在息肉和肿块。五十六例患者（68%）正常。CTC数据进行线性内插，以产生各向同性的数据集，并通过使用知识引导的分割技术提取结肠。两种方法，模糊合并和壁增厚分析，开发了群众的检测。模糊合并方法通过将结肠壁内局部帽状形状的初始CAD检测分离为肿块候选者和息肉候选者来检测具有显著管腔内成分的肿块。壁增厚分析通过搜索结肠壁的异常增厚来检测非腔内肿块。采用基于快速行进算法的水平集方法提取候选块的最终区域。通过二次判别分类器减少假阳性（FP）检测。该方案的性能进行了评估，通过使用留一法（循环）与患者消除。除了从仰卧位和俯卧位的CTC数据集中部分切除的14个肿块中的一个外，所有肿块都被检测到。模糊合并法检测到11个肿块，壁增厚分析检测到3个肿块，包括所有非腔内肿块。结合起来，这两种方法检测到14个肿块中的13个，基于留一法评估，平均每位患者的FP为0.21。大多数FP是由结肠壁的外在压迫产生的，放射科医生很容易快速识别。质量检测方法不影响息肉检测结果。结果表明，该计划是潜在的有用的，在提供一个高性能的CAD计划检测结直肠肿瘤的CTC。(C)2004年美国医学物理学家协会。
In recent years, several computer-aided detection (CAD) schemes have been developed for the detection of polyps in CT colonography (CTC). However, few studies have addressed the problem of computerized detection of colorectal masses in CTC. This is mostly because masses are considered to be well visualized by a radiologist because of their size and invasiveness. Nevertheless, the automated detection of masses would naturally complement the automated detection of polyps in CTC and would produce a more comprehensive computer aid to radiologists. Therefore, in this study, we identified some of the problems involved with the computerized detection of masses, and we developed a scheme for the computerized detection of masses that can be integrated into a CAD scheme for the detection of polyps. The performance of the mass detection scheme was evaluated by application to clinical CTC data sets. CTC was performed on 82 patients with helical CT scanners and reconstruction intervals of 1.0-5.0 mm in the supine and prone positions. Fourteen patients (17%) had a total of 14 masses of 30-50 mm, and sixteen patients (20%) had a total of 30 polyps 5-25 mm in diameter. Four patients had both polyps and masses. Fifty-six of the patients (68%) were normal. The CTC data were interpolated linearly to yield isotropic data sets, and the colon was extracted by use of a knowledge-guided segmentation technique. Two methods, fuzzy merging and wall-thickening analysis, were developed for the detection of masses. The fuzzy merging method detected masses with a significant intraluminal component by separating the initial CAD detections of locally cap-like shapes within the colonic wall into mass candidates and polyp candidates. The wall-thickening analysis detected nonintraluminal masses by searching the colonic wall for abnormal thickening. The final regions of the mass candidates were extracted by use of a level set method based on a fast marching algorithm. False-positive (FP) detections were reduced by a quadratic discriminant classifier. The performance of the scheme was evaluated by use of a leave-one-out (round-robin) method with by-patient elimination. All but one of the 14 masses, which was partially cut off from the CTC data set in both supine and prone positions, were detected. The fuzzy merging method detected 11 of the masses, and the wall-thickening analysis detected 3 of the masses including all nonintraluminal masses. In combination, the two methods detected 13 of the 14 masses with 0.21 FPs per patient on average based on the leave-one-out evaluation. Most FPs were generated by extrinsic compression of the colonic wall that would be recognized easily and quickly by a radiologist. The mass detection methods did not affect the result of the polyp detection. The results indicate that the scheme is potentially useful in providing a high-performance CAD scheme for the detection of colorectal neoplasms in CTC. (C) 2004 American Association of Physicists in Medicine.