Näppi Janne J, Do Synho, Yoshida Hiroyuki
Abdom Imaging (2013). 2013;8198:73-80. doi: 10.1007/978-3-642-41083-3_9.
Reliable computer-aided detection (CADe) of small polyps and flat lesions is limited by the relatively low image resolution of computed tomographic colonography (CTC). We developed a sinogram-based super-resolution (SR) method to enhance the images of lesion candidates detected by CADe. First, CADe is used to detect lesion candidates at high sensitivity from conventional CTC images. Next, the signal patterns of the lesion candidates are enhanced in sinogram domain by use of non-uniform compressive sampling and iterative reconstruction to produce SR images of the lesion candidates. For pilot evaluation, an anthropomorphic phantom including simulated lesions was filled partially with fecal tagging and scanned by use of a CT scanner. A fully automated CADe scheme was used to detect lesion candidates in the images reconstructed at conventional 0.61-mm and at 0.10-mm SR image resolution. The proof-of-concept results indicate that the SR method has potential to reduce the number of FP CADe detections below that obtainable with the conventional CTC imaging technology.
小息肉和平坦病变的可靠计算机辅助检测（CADe）受到计算机断层结肠成像（CTC）相对较低图像分辨率的限制。我们开发了一种基于正弦图的超分辨率（SR）方法，以增强由CADe检测到的病变候选图像。首先，使用CADe从传统CTC图像中高灵敏度地检测病变候选。接下来，通过使用非均匀压缩采样和迭代重建在正弦图域中增强病变候选的信号模式，以生成病变候选的SR图像。为了进行初步评估，一个包含模拟病变的拟人化体模部分填充了粪便标记物，并使用CT扫描仪进行扫描。使用全自动CADe方案在传统0.61毫米和0.10毫米SR图像分辨率下重建的图像中检测病变候选。概念验证结果表明，SR方法有可能将假阳性CADe检测的数量减少到低于传统CTC成像技术可获得的数量。
