Guleng Anette, Bolstad Kirsten, Dalehaug Ingvild, Flatabø Silje, Aadnevik Daniel, Pettersen Helge E S
Department of Oncology and Medical Physics, Haukeland University Hospital, 5021 Bergen, Norway.
Department of Diagnostic Physics, Oslo University Hospital, 0424 Oslo, Norway.
Diagnostics (Basel). 2020 Aug 28;10(9):647. doi: 10.3390/diagnostics10090647.
Iterative reconstruction (IR) is a computed tomgraphy (CT) reconstruction algorithm aiming at improving image quality by reducing noise in the image. During this process, IR also changes the noise properties in the images. To assess how IR algorithms from four vendors affect the noise properties in CT images, an anthropomorphic phantom was scanned and images reconstructed with filtered back projection (FBP), and a medium and high level of IR. Each image acquisition was performed 30 times at the same slice position, to create noise maps showing the inter-image pixel standard deviation through the 30 images. We observed that IR changed the noise properties in the CT images by reducing noise more in homogeneous areas than at anatomical edges between structures of different densities. This difference increased with increasing IR level, and with increasing difference in density between two adjacent structures. Each vendor's IR algorithm showed slightly different noise reduction properties in how much noise was reduced at different positions in the phantom. Users need to be aware of these differences when working with optimization of protocols using IR across scanners from different vendors.
迭代重建（IR）是一种计算机断层扫描（CT）重建算法，旨在通过减少图像噪声来提高图像质量。在此过程中，IR也会改变图像中的噪声特性。为了评估来自四家供应商的IR算法如何影响CT图像中的噪声特性，对一个仿真人体模型进行了扫描，并使用滤波反投影（FBP）以及中等和高水平的IR重建图像。在同一切片位置对每次图像采集进行30次，以创建噪声图，显示通过这30幅图像的图像间像素标准差。我们观察到，IR通过在均匀区域比在不同密度结构之间的解剖边缘处更多地减少噪声，从而改变了CT图像中的噪声特性。这种差异随着IR水平的增加以及两个相邻结构之间密度差异的增加而增大。每个供应商的IR算法在模型不同位置减少的噪声量方面表现出略有不同的降噪特性。当使用来自不同供应商的扫描仪进行IR协议优化时，用户需要了解这些差异。
