Abstract:
Three-dimensional ultrasound has been increasingly considered as a safe radiation-free alternative to radiation-based fluoroscopic imaging for surgical guidance during computer-assisted orthopedic interventions, but because ultrasound images contain significant artifacts, it is challenging to automatically extract bone surfaces from these images. We propose an effective way to extract 3-D bone surfaces using a surface growing approach that is seeded from 2-D bone contours. The initial 2-D bone contours are estimated from a combination of ultrasound strain images and envelope power images. Novel features of the proposed method include: (i) improvement of a previously reported 2-D strain imaging-based bone segmentation method by incorporation of a depth-dependent cumulative power of the envelope into the elastographic data; (ii) incorporation of an echo decorrelation measure-based weight to fuse the strain and envelope maps; (iii) use of local statistics of the bone surface candidate points to detect the presence of any bone discontinuity; and (iv) an extension of our 2-D bone contour into a 3-D bone surface by use of an effective surface growing approach. Our new method produced average improvements in the mean absolute error of 18% and 23%, respectively, on 2-D and 3-D experimental phantom data, compared with those of two state-of-the-art bone segmentation methods. Validation on 2-D and 3-D clinical in vivo data also reveals, respectively, an average improvement in the mean absolute fitting error of 55% and an 18-fold improvement in the computation time.
摘要:
在计算机辅助骨科介入手术期间,三维超声越来越被认为是基于辐射的荧光成像的安全无辐射替代方案,用于手术指导。但是因为超声图像包含明显的伪影,从这些图像中自动提取骨骼表面是具有挑战性的。我们提出了一种有效的方法来使用从2-D骨骼轮廓播种的表面生长方法提取3-D骨骼表面。从超声应变图像和包络功率图像的组合估计初始2-D骨轮廓。所提出的方法的新特征包括:(i)通过将包络的深度相关累积功率合并到弹性成像数据中来改进先前报道的基于二维应变成像的骨骼分割方法;(ii)合并基于回波去相关度量的权重以融合应变和包络图;(iii)使用骨骼表面候选点的局部统计信息来检测任何骨骼不连续性的存在;(iv)通过将我们的3D骨骼表面轮廓扩展到有效的3D方法。我们的新方法产生了18%和23%的平均绝对误差的平均改进,分别,在二维和三维实验体模数据上,与两种最先进的骨骼分割方法相比。对2-D和3-D临床体内数据的验证也揭示了,分别,平均绝对拟合误差平均提高55%,计算时间提高18倍。