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3D Ultrasound-CT Registration in Orthopaedic Trauma Using GMM Registration with Optimized Particle Simulation-Based Data Reduction

机译:使用GMM配准和基于优化的基于粒子模拟的数据归约法在骨科创伤中进行3D超声CT配准

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Accurate real-time registration of intra-operative ultrasound (US) to computed tomography (CT) remains a challenging problem. In orthopedic applications, a recent promising approach proposed the use of Gaussian mixture modeling for bone surface registration. Though relatively successful, the method relied on naive and error prone subsampling of the surfaces registered to reduce computational cost and also heavily relied on heuristically-set parameters for bone surface generation. In this paper, we present an improved approach employing a novel point simplification method that redistributes surface points to better represent the surface achieving near real-time registration with higher accuracy and robustness. We also present a framework for automating the parameter selection in the bone surface extraction step. For validation, we present extensive quantitative tests on phantom and clinical data obtained by scanning patients with pelvic ring fractures in the operating room. We show an 89% average improvement in target registration error over the recent GMM registration based method.
机译:术中超声(US)到计算机断层扫描(CT)的准确实时配准仍然是一个具有挑战性的问题。在骨科应用中,最近有希望的方法提出使用高斯混合模型进行骨表面配准。尽管相对成功,但是该方法依赖于已注册的表面的幼稚和易于出错的二次采样以减少计算成本,并且还严重依赖于启发式设置的参数来生成骨表面。在本文中,我们提出了一种使用新颖的点简化方法的改进方法,该方法可以重新分布表面点,以更好地表示具有更高准确性和鲁棒性的接近实时配准的表面。我们还提出了在骨骼表面提取步骤中自动选择参数的框架。为了进行验证,我们对通过在手术室中扫描骨盆环骨折的患者获得的体模和临床数据进行了广泛的定量测试。与最近的基于GMM注册的方法相比,我们显示出目标注册错误的平均改进幅度为89%。

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