A 3D Image Registration Method for Laparoscopic Liver Surgery Navigation

Abstract

At present, laparoscopic augmented reality (AR) navigation has been applied to minimally invasive abdominal surgery, which can help doctors to see the location of blood vessels and tumors in organs, so as to perform precise surgery operations. Image registration is the process of optimally mapping one or more images to the target image, and it is also the core of laparoscopic AR navigation. The key is how to shorten the registration time and optimize the registration accuracy. We have studied the three-dimensional (3D) image registration technology in laparoscopic liver surgery navigation and proposed a new registration method combining rough registration and fine registration. First, the adaptive fireworks algorithm (AFWA) is applied to rough registration, and then the optimized iterative closest point (ICP) algorithm is applied to fine registration. We proposed a method that is validated by the computed tomography (CT) dataset 3D-IRCADb-01. Experimental results show that our method is superior to other registration methods based on stochastic optimization algorithms in terms of registration time and accuracy.