A fast stereo matching algorithm for 3D reconstruction of internal organs in laparoscopic surgery

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.