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

机译:GPU加速登记腰椎的统计形状模型到3D超声图像

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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:我们呈现了垂直垂直(L2-L4)的3D超声图像的统计形状模型注册的平行实现。协方差矩阵适配演化策略优化技术,以及线性组合相似度量的线性相关性,提高了登记方法的鲁棒性和捕获范围。在图形处理单元上实现了实例化和超声模拟,以便更快地注册。 Phantom研究表明,平均目标登记误差为3.2 mm,而所有情况的80%的含量为3.5mm以下的目标登记误差。

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