Artery Segmentation in Ultrasound Images Based on an Evolutionary Scheme

Abstract

Segmentation in ultrasound (US) images is a challenge in computer vision, due to the high signal noise, artifacts that produce discontinuities in the boundaries and shadows that hide part of the received signal. In this paper, a solution based on ellipse fitting motivated by natural artery geometry will be proposed. To optimize the parameters that define such an ellipse, a strategy based on an evolutionary algorithm was adopted. The paper will also demonstrate that the method can be solved in a reasonable amount of time, making intensive GPGPU (general graphics processing unit, GPU, processing) where excellent computing performance gain is obtained (up to 54 times faster than the parallel CPU implementation). The proposed approach is compared with other artery segmentation methods in US images, obtaining very promising results. Furthermore, the proposed approach is parameter free and does not require any initialization estimation close to the final solution.