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使用主动标记物进行任意头部运动的前瞻性实时校正。

Prospective real-time correction for arbitrary head motion using active markers.

机构信息

Department of Biomedical Engineering, Columbia University, New York, New York 10032, USA.

出版信息

Magn Reson Med. 2009 Oct;62(4):943-54. doi: 10.1002/mrm.22082.

Abstract

Patient motion during an MRI exam can result in major degradation of image quality, and is of increasing concern due to the aging population and its associated diseases. This work presents a general strategy for real-time, intraimage compensation of rigid-body motion that is compatible with multiple imaging sequences. Image quality improvements are established for structural brain MRI acquired during volunteer motion. A headband integrated with three active markers is secured to the forehead. Prospective correction is achieved by interleaving a rapid track-and-update module into the imaging sequence. For every repetition of this module, a short tracking pulse-sequence remeasures the marker positions; during head motion, the rigid-body transformation that realigns the markers to their initial positions is fed back to adaptively update the image-plane-maintaining it at a fixed orientation relative to the head-before the next imaging segment of k-space is acquired. In cases of extreme motion, corrupted lines of k-space are rejected and reacquired with the updated geometry. High-precision tracking measurements (0.01 mm) and corrections are accomplished in a temporal resolution (37 ms) suitable for real-time application. The correction package requires minimal additional hardware and is fully integrated into the standard user interface, promoting transferability to clinical practice.

摘要

患者在磁共振成像(MRI)检查过程中的运动会导致图像质量的严重下降,并且由于人口老龄化及其相关疾病,这种情况越来越受到关注。本研究提出了一种通用的实时、图像内刚体运动补偿策略,适用于多种成像序列。通过对志愿者运动期间采集的结构性脑 MRI 进行图像质量改进,验证了该方法的有效性。在额头上固定一个集成了三个主动标记的头带。通过在成像序列中交错快速跟踪和更新模块来实现前瞻性校正。对于该模块的每次重复,一个短的跟踪脉冲序列重新测量标记的位置;在头部运动期间,将重新对齐标记到其初始位置的刚体变换反馈到自适应更新图像平面,以在获取下一个 k 空间成像段之前将其保持在相对于头部的固定方向。在极端运动的情况下,会拒绝被污染的 k 空间线,并使用更新的几何形状重新获取。高精度跟踪测量(0.01 毫米)和校正可以在适合实时应用的时间分辨率(37 毫秒)内完成。校正包所需的额外硬件最少,并且完全集成到标准用户界面中,有利于向临床实践的转移。

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