首页> 外文会议>Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2011 IEEE >Real-time respiratory motion correction for simultaneous PET-MR using an MR-derived motion model
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Real-time respiratory motion correction for simultaneous PET-MR using an MR-derived motion model

机译:使用MR衍生的运动模型对PET-MR进行实时呼吸运动校正

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Respiratory motion during PET imaging causes the resulting PET images to become corrupted by artefacts. In this paper we describe a technique for motion-correction of PET data based on MR imaging that is suitable for use in a simultaneous PET-MR imaging system. The technique is based on the formation of a subject-specific respiratory motion model from near real-time dynamic MR images and is capable of making real-time motion estimates based on a one-dimensional MR navigator, allowing additional MR imaging to take place at the same time as PET imaging. The model estimates the complex freeform deformations present in the human thorax during respiration. We validate our motion compensation approach using PET simulations based on real MR data of the thorax acquired from a healthy volunteer. Qualitative results show a clear improvement in visualisation of the myocardium and three tumours that were artificially added to the emission/attenuation map of the volunteer close to the diaphragm. Quantitative analysis was based on computing DICE coefficients between true regions of interest (myocardium and the three artificial tumours) and regions manually segmented from a ‘no motion’ PET image, an uncorrected PET image and a motion-corrected PET image. The DICE coefficients over all 4 regions were 0.8 ± 0.03 (‘no motion’), 0.24 ± 0.11 (uncorrected) and 0.6 ± 0.08 (corrected), indicating that a significant improvement in PET resolution and quantification is achievable by applying our motion-correction technique.
机译:PET成像期间的呼吸运动会导致生成的PET图像被伪影破坏。在本文中,我们描述了一种基于MR成像的PET数据运动校正技术,该技术适用于同步PET-MR成像系统。该技术基于从近实时动态MR图像形成特定对象的呼吸运动模型,并且能够基于一维MR导航器进行实时运动估计,从而允许在以下位置进行附加MR成像与PET成像同时进行。该模型估计呼吸过程中人胸中存在的复杂的自由形式变形。我们基于从健康志愿者那里获得的胸部真实MR数据,使用PET模拟验证了我们的运动补偿方法。定性结果显示心肌和三个肿瘤的可视化明显改善,这三个肿瘤被人工添加到靠近隔膜的志愿者的发射/衰减图上。定量分析是基于计算真正感兴趣的区域(心肌和三个人工肿瘤)与从“无运动” PET图像,未校正的PET图像和经运动校正的PET图像手动分割的区域之间的DICE系数。所有4个区域的DICE系数分别为0.8±0.03(“无运动”),0.24±0.11(未校正)和0.6±0.08(校正),这表明通过应用我们的运动校正可以显着提高PET分辨率和定量技术。

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