Fast and accurate vision‐based stereo reconstruction and motion estimation for image‐guided liver surgery

Abstract

Image-guided liver surgery aims to enhance the precision of resection and ablation by providing fast localisation of tumours and adjacent complex vasculature to improve oncologic outcome. This Letter presents a novel end-to-end solution for fast stereo reconstruction and motion estimation that demonstrates high accuracy with phantom and clinical data. The authors’ computationally efficient coarse-to-fine (CTF) stereo approach facilitates liver imaging by accounting for low texture regions, enabling precise three-dimensional (3D) boundary recovery through the use of adaptive windows and utilising a robust 3D motion estimator to reject spurious data. To the best of their knowledge, theirs is the only adaptive CTF matching approach to reconstruction and motion estimation that registers time series of reconstructions to a single key frame for registration to a volumetric computed tomography scan. The system is evaluated empirically in controlled laboratory experiments with a liver phantom and motorised stages for precise quantitative evaluation. Additional evaluation is provided through testing with patient data during liver resection.

Application of Three-Dimensional Image Reconstruction Technology in Neurogenic Intestinal Nursing Tasks

“…Image quality is the basis of image algorithm, and the quality of image directly affects the effect of the algorithm [9,10]. Before the implementation of image correlation algorithm, it is necessary to preprocess the image to suppress the useless information in the image and enhance the relevant information of the tested object [11,12].…”