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用于MRI中光学前瞻性头部运动校正的自编码标记物。

Self-encoded marker for optical prospective head motion correction in MRI.

作者信息

Forman Christoph, Aksoy Murat, Hornegger Joachim, Bammer Roland

机构信息

Department of Radiology, Stanford University, Stanford, California, USA.

出版信息

Med Image Comput Comput Assist Interv. 2010;13(Pt 1):259-66. doi: 10.1007/978-3-642-15705-9_32.

Abstract

The tracking and compensation of patient motion during a magnetic resonance imaging (MRI) acqusition is an unsolved problem. For brain MRI, a promising approach recently suggested is to track the patient using an in-bore camera and a checkerboard marker attached to the patient's forehead. However, the possible tracking range of the head pose is limited by the locally attached marker that must be entirely visible inside the camera's narrow field of view (FOV). To overcome this shortcoming, we developed a novel self-encoded marker where each feature on the pattern is augmented with a 2-D barcode. Hence, the marker can be tracked even if it is not completely visible in the camera image. Furthermore, it offers considerable advantages over the checkerboard marker in terms of processing speed, since it makes the correspondence search of feature points and marker-model coordinates, which are required for the pose estimation, redundant. The motion correction with the novel self-encoded marker recovered a rotation of 18 degrees around the principal axis of the cylindrical phantom in-between two scans. After rigid registration of the resulting volumes, we measured a maximal error of 0.39 mm and 0.15 degrees in translation and rotation, respectively. In in-vivo experiments, the motion compensated images in scans with large motion during data acquisition indicate a correlation of 0.982 compared to a corresponding motion-free reference.

摘要

在磁共振成像(MRI)采集过程中对患者运动进行跟踪和补偿是一个尚未解决的问题。对于脑部MRI,最近提出的一种有前景的方法是使用孔内相机和附着在患者前额的棋盘格标记来跟踪患者。然而,头部姿势的可能跟踪范围受到局部附着标记的限制,该标记必须在相机的狭窄视野(FOV)内完全可见。为了克服这一缺点,我们开发了一种新型的自编码标记,其中图案上的每个特征都增加了一个二维条形码。因此,即使该标记在相机图像中未完全可见,也可以对其进行跟踪。此外,在处理速度方面,它比棋盘格标记具有相当大的优势,因为它使得姿态估计所需的特征点与标记模型坐标的对应搜索变得多余。使用新型自编码标记进行的运动校正恢复了两次扫描之间圆柱形模型围绕主轴18度的旋转。在对所得体积进行刚性配准后,我们分别测量了平移和旋转的最大误差为0.39毫米和0.15度。在体内实验中,与相应的无运动参考相比,数据采集期间具有大运动的扫描中的运动补偿图像的相关性为0.982。

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