Skornitzke Stephan, Raddatz Jacek, Bahr André, Pahn Gregor, Kauczor Hans-Ulrich, Stiller Wolfram
Diagnostic and Interventional Radiology (DIR), Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120, Heidelberg, Germany.
Institut für Geowissenschaften, J. W. Goethe-Universität, Frankfurt am Main, Germany.
Eur Radiol Exp. 2019 Mar 12;3(1):12. doi: 10.1186/s41747-019-0091-8.
In computed tomography (CT) quality assurance, alignment of image quality phantoms is crucial for quantitative and reproducible evaluation and may be improved by alignment correction. Our goal was to develop an alignment correction algorithm to facilitate geological sampling of sediment cores taken from a cold-water coral mount.
An alignment correction algorithm was developed and tested with a CT acquisition at 120 kVp and 150 mAs of an image quality phantom. Random translation (maximum 15 mm) and rotation (maximum 2.86°) were applied and ground-truth was compared to parameters determined by alignment correction. Furthermore, mean densities were evaluated in four regions of interest (ROIs) placed in the phantom low-contrast section, comparing values before and after correction to ground truth. This process was repeated 1000 times. After validation, alignment correction was applied to CT acquisitions (140 kVp, 570 mAs) of sediment core sections up to 1 m in length, and sagittal reconstructions were calculated for sampling planning.
In the phantom, average absolute differences between applied and detected parameters after alignment correction were 0.01 ± 0.06 mm (mean ± standard deviation) along the x-axis, 0.11 ± 0.08 mm along the y-axis, 0.15 ± 0.07° around the x-axis, and 0.02 ± 0.02° around the y-axis, respectively. For ROI analysis, differences in densities were 63.12 ± 30.57, 31.38 ± 32.10, 18.27 ± 35.57, and 9.59 ± 26.37 HU before alignment correction and 1.22 ± 1.40, 0.76 ± 0.9, 0.45 ± 0.86, and 0.36 ± 0.48 HU after alignment correction, respectively. For sediment core segments, average absolute detected parameters were 3.93 ± 2.89 mm, 7.21 ± 2.37 mm, 0.37 ± 0.33°, and 0.21 ± 0.22°, respectively.
The alignment correction algorithm was successfully evaluated in the phantom and allowed a correct alignment of sediment core segments, thus aiding in sampling planning. Application to other tasks, like image quality analysis, seems possible.
在计算机断层扫描（CT）质量保证中，图像质量体模的对齐对于定量和可重复评估至关重要，并且可以通过对齐校正来改善。我们的目标是开发一种对齐校正算法，以促进对取自冷水珊瑚礁的沉积物岩芯进行地质采样。
开发了一种对齐校正算法，并使用图像质量体模在120 kVp和150 mAs条件下进行CT采集进行测试。应用随机平移（最大15 mm）和旋转（最大2.86°），并将真实值与通过对齐校正确定的参数进行比较。此外，在体模低对比度区域放置的四个感兴趣区域（ROI）中评估平均密度，将校正前后的值与真实值进行比较。此过程重复1000次。验证后，将对齐校正应用于长度达1 m的沉积物岩芯段的CT采集（140 kVp，570 mAs），并计算矢状面重建以进行采样规划。
在体模中，对齐校正后应用参数与检测参数之间的平均绝对差异在x轴上为0.01±0.06 mm（平均值±标准差），在y轴上为0.11±0.08 mm，绕x轴为0.15±0.07°，绕y轴为0.02±0.02°。对于ROI分析，对齐校正前密度差异分别为63.12±30.57、31.38±32.10、18.27±35.57和9.59±26.37 HU，对齐校正后分别为1.22±1.40、0.76±0.9、0.45±0.86和0.36±0.48 HU。对于沉积物岩芯段，平均绝对检测参数分别为3.93±2.89 mm、7.21±2.37 mm、0.37±0.33°和0.21±0.22°。
对齐校正算法在体模中得到成功评估，并能对沉积物岩芯段进行正确对齐，从而有助于采样规划。该算法应用于其他任务（如图像质量分析）似乎也是可行的。
