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Effective One Step-iterative Fiducial Marker-based Compensation for Involuntary Motion in Weight-bearing C-arm Cone-beam CT Scanning of Knees

机译:有效的基于一步迭代基准标记的负重C型臂锥束CT扫描中的非自愿运动补偿

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We previously introduced three different fiducial marker-based correction methods (2D projection shifting, 2D projection warping, and 3D image warping) for patients' involuntary motion in the lower body during weight-bearing C-arm CT scanning. The 3D warping method performed better than 2D methods since it could more accurately take into account the lower body motion in 3D. However, as the 3D warping method applies different rotational and translational movement to the reconstructed image for each projection frame, distance-related weightings were slightly twisted and thus result in overlaying background noise over the entire image. In order to suppress background noise and artifacts (e.g. metallic marker-caused streaks), the 3D warping method has been improved by incorporating bilateral filtering and a Landweber-type iteration in one step. A series of projection images of five healthy volunteers standing at various flexion angles were acquired using a C-arm cone-beam CT system with a flat panel. A horizontal scanning trajectory of the C-arm was calibrated to generate projection matrices. Using the projection matrices, the static reference marker coordinates in 3D were estimated and used for the improved 3D warping method. The improved 3D warping method effectively reduced background noise down below the noise level of 2D methods and also eliminated metal-generated streaks. Thus, improved visibility of soft tissue structures (e.g. fat and muscle) was achieved while maintaining sharp edges at bone-tissue interfaces. Any high resolution weight-bearing cone-beam CT system can apply this method for motion compensation.
机译:我们先前介绍负重C型臂扫描CT期间病人的下半身运动不自主三个不同的基准基于标记的校正方法(2D投影转换,2D投影翘曲和3D图像变形)。 3D翘曲方法比2D方法更好,因为它可以更准确地考虑3D的下半身运动。然而,当3D翘曲方法将不同的旋转和平移运动应用于每个投影帧的重建图像时,距离相关的配件略微扭曲,因此导致整个图像上覆盖背景噪声。为了抑制背景噪声和伪像(例如金属标记导致条纹),通过在一步中结合双边过滤和Landwoer型迭代,改善了3D翘曲方法。使用具有平板的C形臂锥形梁CT系统获取站立在各种屈曲角度的五个健康志愿者的一系列投影图像。 C形臂的水平扫描轨迹被校准以产生投影矩阵。使用投影矩阵,估计3D中的静态参考标记坐标并用于改进的3D翘曲方法。改进的3D翘曲方法有效地降低了2D方法的噪声水平的背景噪声,并且还消除了金属产生的条纹。因此,在保持骨组织界面处的尖锐边缘的同时实现了软组织结构(例如脂肪和肌肉)的改善的可见性。任何高分辨率负重锥形梁CT系统都可以应用这种用于运动补偿的方法。

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