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首页> 外文会议>International Conference on Medical Image Computing and Computer-Assisted Intervention(MICCAI 2004) pt.2; 20040926-29; Saint-Malo(FR) >A Novel Approach to Anatomical Structure Morphing for Intraoperative Visualization
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A Novel Approach to Anatomical Structure Morphing for Intraoperative Visualization

机译：术中可视化的解剖结构变形的新方法

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In computer assisted surgery 3D models are now routinely used to plan and navigate a surgery. These models enhance the surgeon's capability to decrease the invasiveness of surgical procedures and increase their accuracy and safety. Models obtained from specifically acquired CT scans have the disadvantage that they induce high radiation dose to the patient. In this paper we propose a novel method to construct a patient-specific model that provides an appropriate intra-operative 3D visualization without the need for a pre or intra-operative imaging. The 3D model is reconstructed by fitting a statistical deformable model to minimal sparse 3D data consisting of digitized landmarks and surface points that are obtained intra-operatively. The statistical model is constructed using Principal Component Analysis from training objects. Our morphing method then computes a Mahalanobis distance weighted least square fit of the model by solving a linear equation system. The refined morphing scheme has better convergence behaviour because of the additional parameter that relaxes the Mahalanobis distance term as additional points are incorporated. We present leave-one-out experiments with model generated from proximal femors and hippocampi.
机译：在计算机辅助手术中，现在通常使用3D模型来计划和导航手术。这些模型增强了外科医生减少外科手术侵入性并提高准确性和安全性的能力。从专门获得的CT扫描获得的模型具有以下缺点：它们会向患者产生高辐射剂量。在本文中，我们提出了一种新颖的方法来构建特定于患者的模型，该模型可提供适当的术中3D可视化，而无需术前或术中成像。通过将统计可变形模型拟合到最小化的稀疏3D数据来重建3D模型，稀疏3D数据由术中获得的数字化界标和表面点组成。使用主成分分析从训练对象构建统计模型。然后，我们的变形方法通过求解线性方程组来计算模型的马氏距离加权最小二乘拟合。精巧的变形方案具有更好的收敛性能，这是因为当合并了其他点时，该参数使Mahalanobis距离项松弛。我们目前采用从股骨近端和海马体产生的模型进行一劳永逸的实验。

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