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A Fast Stereo Matching Algorithm for 3D Reconstruction of Internal Organs in Laparoscopic Surgery

机译:腹腔镜手术中内脏三维重建快速立体声匹配算法

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We propose a fast stereo matching algorithm for 3D reconstruction of internal organs using a stereoscopic laparoscope. Stoyanov et al. have proposed a technique for recovering the 3D depth of internal organs from images taken by a stereoscopic laparoscope. In their technique, the dense stereo correspondence is solved by registration of the entire image. However, the computational cost is very high because registration of the entire image requires multidimensional optimization. In this paper, we propose a new algorithm based on a local area registration method that requires only low-dimensional optimization for reduction of computational cost. We evaluated the computational cost of the proposed algorithm using a stereoscopic laparoscope. We also evaluated the accuracy of the proposed algorithm using three types of images of abdominal models taken by a 3D laser scanner. In the matching step, the size of the template used to calculate the correlation coefficient, on which the computational cost is strongly dependent, was reduced by a factor of 16 as compared with the conventional algorithm. On the other hand, the average depth errors were 4.68 mm, 7.18 mm, and 7.44 mm respectively, and accuracy was approximately as same as the conventional algorithm.
机译:我们提出了一种快速立体声匹配算法,用于使用立体腹腔镜的内部器官的三维重建。 Stoyanov等人。提出了一种用于从立体腹腔镜拍摄的图像中恢复内部器官的3D深度的技术。在其技术中,密集的立体声对应通过整个图像的登记解决。然而,计算成本非常高,因为整个图像的登记需要多维优化。在本文中,我们提出了一种基于局域注册方法的新算法,该算法仅需要低维优化来降低计算成本。我们使用立体腹腔镜评估了所提出的算法的计算成本。我们还使用3D激光扫描仪采取的三种类型的腹部模型图像评估所提出的算法的准确性。在匹配步骤中,与传统算法相比,用于计算相关系数的模板的大小,在其上依赖计算成本强烈依赖于其强度。另一方面,平均深度误差分别为4.68毫米,7.18毫米和7.44mm,准确性大致与传统算法一样其。

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