Abstract：
OBJECTIVE: Head motions during brain PET scan cause degradation of brain images, but head fixation or external-maker attachment become burdensome on patients. Therefore, we have developed a motion correction method that uses a 3D face-shape model generated by a range-sensing camera (Kinect) and by CT images. We have successfully corrected the PET images of a moving mannequin-head phantom containing radioactivity. Here, we conducted a volunteer study to verify the effectiveness of our method for clinical data.
METHODS: Eight healthy men volunteers aged 22-45 years underwent a 10-min head-fixed PET scan as a standard of truth in this study, which was started 45 min after 18F-fluorodeoxyglucose (285 ± 23 MBq) injection, and followed by a 15-min head-moving PET scan with the developed Kinect based motion-tracking system. First, selecting a motion-less period of the head-moving PET scan provided a reference PET image. Second, CT images separately obtained on the same day were registered to the reference PET image, and create a 3D face-shape model, then, to which Kinect-based 3D face-shape model matched. This matching parameter was used for spatial calibration between the Kinect and the PET system. This calibration parameter and the motion-tracking of the 3D face shape by Kinect comprised our motion correction method. The head-moving PET with motion correction was compared with the head-fixed PET images visually and by standard uptake value ratios (SUVRs) in the seven volume-of-interest regions. To confirm the spatial calibration accuracy, a test-retest experiment was performed by repeating the head-moving PET with motion correction twice where the volunteer\'s pose and the sensor\'s position were different.
RESULTS: No difference was identified visually and statistically in SUVRs between the head-moving PET images with motion correction and the head-fixed PET images. One of the small nuclei, the inferior colliculus, was identified in the head-fixed PET images and in the head-moving PET images with motion correction, but not in those without motion correction. In the test-retest experiment, the SUVRs were well correlated (determinant coefficient, r2 = 0.995).
CONCLUSIONS: Our motion correction method provided good accuracy for the volunteer data which suggested it is useable in clinical settings.
METHODS: Eight healthy men volunteers aged 22-45 years underwent a 10-min head-fixed PET scan as a standard of truth in this study, which was started 45 min after 18F-fluorodeoxyglucose (285 ± 23 MBq) injection, and followed by a 15-min head-moving PET scan with the developed Kinect based motion-tracking system. First, selecting a motion-less period of the head-moving PET scan provided a reference PET image. Second, CT images separately obtained on the same day were registered to the reference PET image, and create a 3D face-shape model, then, to which Kinect-based 3D face-shape model matched. This matching parameter was used for spatial calibration between the Kinect and the PET system. This calibration parameter and the motion-tracking of the 3D face shape by Kinect comprised our motion correction method. The head-moving PET with motion correction was compared with the head-fixed PET images visually and by standard uptake value ratios (SUVRs) in the seven volume-of-interest regions. To confirm the spatial calibration accuracy, a test-retest experiment was performed by repeating the head-moving PET with motion correction twice where the volunteer\'s pose and the sensor\'s position were different.
RESULTS: No difference was identified visually and statistically in SUVRs between the head-moving PET images with motion correction and the head-fixed PET images. One of the small nuclei, the inferior colliculus, was identified in the head-fixed PET images and in the head-moving PET images with motion correction, but not in those without motion correction. In the test-retest experiment, the SUVRs were well correlated (determinant coefficient, r2 = 0.995).
CONCLUSIONS: Our motion correction method provided good accuracy for the volunteer data which suggested it is useable in clinical settings.
摘要：
目的：脑部PET扫描过程中的头部运动会导致脑部图像退化，但头部固定或外部制造商附件成为病人的负担。因此,我们开发了一种运动校正方法，该方法使用由距离感应相机（Kinect）和CT图像生成的3D人脸形状模型。我们已经成功地校正了含有放射性的运动人体模型头部体模的PET图像。这里,我们进行了一项志愿者研究,以验证我们的方法对临床数据的有效性.
方法：8名年龄在22-45岁的健康男性志愿者接受了10分钟的头部固定PET扫描，作为本研究的标准。18F-氟代脱氧葡萄糖（285±23MBq）注射后45分钟开始，然后使用开发的基于Kinect的运动跟踪系统进行15分钟的头部移动PET扫描。首先,选择头部移动PET扫描的无运动周期提供参考PET图像。第二,将同一天分别获得的CT图像与参考PET图像进行配准，并创建一个3D人脸模型，然后,基于Kinect的3D人脸形状模型与之匹配。该匹配参数用于Kinect和PET系统之间的空间校准。此校准参数和Kinect对3D面部形状的运动跟踪包括我们的运动校正方法。在视觉上并通过七个感兴趣体积区域中的标准摄取值比率（SUVR）将带有运动校正的头部移动PET与头部固定PET图像进行比较。为了确认空间校准的准确性，在志愿者的姿势和传感器的位置不同的情况下,通过将头部移动PET与运动校正重复两次进行测试-再测试实验.
结果：在带有运动校正的头部移动PET图像和头部固定PET图像之间，在SUVR中没有视觉和统计学上的差异。其中一个小原子核，下丘，在头部固定的PET图像和头部移动的PET图像中进行运动校正，但不是在那些没有运动校正。在重测实验中，SUVR相关性很好(行列式系数，r2=0.995)。
结论：我们的运动校正方法为志愿者数据提供了良好的准确性，这表明它可用于临床环境。
方法：8名年龄在22-45岁的健康男性志愿者接受了10分钟的头部固定PET扫描，作为本研究的标准。18F-氟代脱氧葡萄糖（285±23MBq）注射后45分钟开始，然后使用开发的基于Kinect的运动跟踪系统进行15分钟的头部移动PET扫描。首先,选择头部移动PET扫描的无运动周期提供参考PET图像。第二,将同一天分别获得的CT图像与参考PET图像进行配准，并创建一个3D人脸模型，然后,基于Kinect的3D人脸形状模型与之匹配。该匹配参数用于Kinect和PET系统之间的空间校准。此校准参数和Kinect对3D面部形状的运动跟踪包括我们的运动校正方法。在视觉上并通过七个感兴趣体积区域中的标准摄取值比率（SUVR）将带有运动校正的头部移动PET与头部固定PET图像进行比较。为了确认空间校准的准确性，在志愿者的姿势和传感器的位置不同的情况下,通过将头部移动PET与运动校正重复两次进行测试-再测试实验.
结果：在带有运动校正的头部移动PET图像和头部固定PET图像之间，在SUVR中没有视觉和统计学上的差异。其中一个小原子核，下丘，在头部固定的PET图像和头部移动的PET图像中进行运动校正，但不是在那些没有运动校正。在重测实验中，SUVR相关性很好(行列式系数，r2=0.995)。
结论：我们的运动校正方法为志愿者数据提供了良好的准确性，这表明它可用于临床环境。
