Registration-based Image Segmentation using Lattice Boltzmann Method

Abstract

Image segmentation is the first and important step leading to image analysis and interpretation. Using image segmentation we can divide the image into different regions. In this study, a Lattice Boltzmann model is proposed for registration-based CTA segmentation. The energy model is established and can be minimized by variational method. The gradient descent flow was solved by the Lattice Boltzmann method. In the experiments, a reference image was selected from CTA image series and artificially segmented by experts. By aligning the images to the reference image, the bias of the voxels are obtained. At the same time the contours of the desired object are estimated at the low contrast region.