Arnold Patrik, Preiswerk Frank, Fasel Beat, Salomir Rares, Scheffler Klaus, Cattin Philippe C
Medical Image Analysis Center, University of Basel, 4000 Basel, Switzerland.
Med Image Comput Comput Assist Interv. 2011;14(Pt 2):623-30. doi: 10.1007/978-3-642-23629-7_76.
MR-guided High Intensity Focused Ultrasound is an emerging non-invasive technique capable of depositing sharply localised energy deep within the body, without affecting the surrounding tissues. This, however, implies exact knowledge of the target's position when treating mobile organs. In this paper we present an atlas-based prediction technique that trains an atlas from time-resolved 3D volumes using 4DMRI, capturing the full patient specific motion of the organ. Based on a breathing signal, the respiratory state of the organ is then tracked and used to predict the target's future position. To additionally compensate for the non-periodic slower organ drifts, the static motion atlas is combined with a population-based statistical exhalation drift model. The proposed method is validated on organ motion data of 12 healthy volunteers. Experiments estimating the future position of the entire liver result in an average prediction error of 1.1 mm over time intervals of up to 13 minutes.
磁共振引导高强度聚焦超声是一种新兴的非侵入性技术，能够在不影响周围组织的情况下，将高度聚焦的能量沉积到身体深处。然而，这意味着在治疗移动器官时需要精确了解目标位置。在本文中，我们提出了一种基于图谱的预测技术，该技术使用4D磁共振成像从时间分辨的三维体积中训练图谱，捕捉器官特定于患者的完整运动。基于呼吸信号，然后跟踪器官的呼吸状态并用于预测目标的未来位置。为了额外补偿非周期性的较慢器官漂移，将静态运动图谱与基于群体的统计呼气漂移模型相结合。所提出的方法在12名健康志愿者的器官运动数据上得到了验证。对整个肝脏未来位置进行估计的实验表明，在长达13分钟的时间间隔内，平均预测误差为1.1毫米。
