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首页> 外文期刊>Medical image analysis >Instantiation and registration of statistical shape models of the femur and pelvis using 3D ultrasound imaging.
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Instantiation and registration of statistical shape models of the femur and pelvis using 3D ultrasound imaging.

机译:使用3D超声成像实例化和注册股骨和骨盆的统计形状模型。

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Statistical shape modelling potentially provides a powerful tool for generating patient-specific, 3D representations of bony anatomy for computer-aided orthopaedic surgery (CAOS) without the need for a preoperative CT scan. Furthermore, freehand 3D ultrasound (US) provides a non-invasive method for digitising bone surfaces in the operating theatre that enables a much greater region to be sampled compared with conventional direct-contact (i.e., pointer-based) digitisation techniques. In this paper, we describe how these approaches can be combined to simultaneously generate and register a patient-specific model of the femur and pelvis to the patient during surgery. In our implementation, a statistical deformation model (SDM) was constructed for the femur and pelvis by performing a principal component analysis on the B-spline control points that parameterise the freeform deformations required to non-rigidly register a training set of CT scans to a carefully segmented template CT scan. The segmented template bone surface, represented by a triangulated surface mesh, is instantiated and registered to a cloud of US-derived surface points using an iterative scheme in which the weights corresponding to the first five principal modes of variation of the SDM are optimised in addition to the rigid-body parameters. The accuracy of the method was evaluated using clinically realistic data obtained on three intact human cadavers (three whole pelves and six femurs). For each bone, a high-resolution CT scan and rigid-body registration transformation, calculated using bone-implanted fiducial markers, served as the gold standard bone geometry and registration transformation, respectively. After aligning the final instantiated model and CT-derived surfaces using the iterative closest point (ICP) algorithm, the average root-mean-square distance between the surfaces was 3.5mm over the whole bone and 3.7mm in the region of surgical interest. The corresponding distances after aligning the surfaces using the marker-based registration transformation were 4.6 and 4.5mm, respectively. We conclude that despite limitations on the regions of bone accessible using US imaging, this technique has potential as a cost-effective and non-invasive method to enable surgical navigation during CAOS procedures, without the additional radiation dose associated with performing a preoperative CT scan or intraoperative fluoroscopic imaging. However, further development is required to investigate errors using error measures relevant to specific surgical procedures.
机译:统计形状建模潜在地提供了一种强大的工具,可以为计算机辅助骨科手术(CAOS)生成特定于患者的骨解剖结构的3D表示,而无需术前CT扫描。此外,徒手3D超声(US)提供了一种用于在手术室中数字化骨表面的非侵入性方法,与传统的直接接触(即,基于指针的)数字化技术相比,该方法能够对更大的区域进行采样。在本文中,我们描述了如何结合使用这些方法,以在手术过程中同时生成并注册患者特定的股骨和骨盆模型。在我们的实现中,通过对B样条控制点执行主成分分析来构造股骨和骨盆的统计变形模型(SDM),该参数设定了将非严格的CT扫描训练集注册为A所需的自由变形的参数仔细分割模板CT扫描。实例化由三角表面网格表示的分割后的模板骨骼表面,并使用迭代方案将其注册到US派生的表面点云中,该迭代方案还优化了与SDM的前五个主要变化模式相对应的权重刚体参数。使用在三个完整的人体尸体(三个完整的骨盆和六个股骨)上获得的临床实际数据评估了该方法的准确性。对于每个骨骼,使用骨骼植入的基准标记计算出的高分辨率CT扫描和刚体配准变换分别用作黄金标准的骨骼几何形状和配准变换。使用迭代最近点(ICP)算法对齐最终实例化模型和CT衍生的表面后,表面之间的平均均方根距离在整个骨骼上为3.5mm,而在手术区域则为3.7mm。使用基于标记的配准转换对齐表面后,相应的距离分别为4.6和4.5mm。我们得出的结论是,尽管使用US成像可进入的骨骼区域受到限制,但该技术作为一种低成本且无创的方法具有潜力,可以在CAOS手术期间进行手术导航,而无需进行术前CT扫描或术中透视检查。但是,需要进一步开发以使用与特定手术程序相关的错误度量来调查错误。

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