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GPU Accelerated Registration of a Statistical Shape Model of the Lumbar Spine to 3D Ultrasound Images

机译:GPU加速了腰椎统计形状模型向3D超声图像的配准

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摘要

We present a parallel implementation of a statistical shape model registration to 3D ultrasound images of the lumbar vertebrae (L2-L4). Covariance Matrix Adaptation Evolution Strategy optimization technique, along with Linear Correlation of Linear Combination similarity metric have been used, to improve the robustness and capture range of the registration approach. Instantiation and ultrasound simulation have been implemented on a graphics processing unit for a faster registration. Phantom studies show a mean target registration error of 3.2 mm, while 80% of all the cases yield target registration error of below 3.5 mm.
机译:我们提出统计形状模型配准到腰椎(L2-L4)的3D超声图像的并行实现。使用协方差矩阵适应进化策略优化技术以及线性组合相似度度量的线性相关性,以提高配准方法的鲁棒性和捕获范围。实例化和超声仿真已在图形处理单元上实现,以加快注册速度。幻影研究显示平均目标配准误差为3.2毫米,而所有案例中的80%产生的目标配准误差在3.5毫米以下。

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