Next Article in Journal / Special Issue
Molecular Imaging of Bacterial Infections in vivo: The Discrimination between Infection and Inflammation
Previous Article in Journal
Using Collaborative Tagging for Text Classification: From Text Classification to Opinion Mining
Informatics 2014, 1(1), 52-71; doi:10.3390/informatics1010052

Artery Segmentation in Ultrasound Images Based on an Evolutionary Scheme

1,* , 2
1 Department of Computer Architecture and Technology, ETSI Informática y de Telecomunicación, CITIC-UGR, University of Granada, Granada, E-18071, Spain 2 Hospital Universitario San Cecilio, Servicio de Angiología y Cirugía Vascular, Granada, E-18012, Spain
* Author to whom correspondence should be addressed.
Received: 22 November 2013 / Revised: 16 January 2014 / Accepted: 6 February 2014 / Published: 25 February 2014
(This article belongs to the Special Issue Biomedical Imaging and Visualization)
View Full-Text   |   Download PDF [1247 KB, 26 February 2014; original version 25 February 2014]   |  


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.
Keywords: vision; ultrasound; evolutionary algorithm; segmentation; GPU vision; ultrasound; evolutionary algorithm; segmentation; GPU
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote |
MDPI and ACS Style

Guzman, P.; Ros, R.; Ros, E. Artery Segmentation in Ultrasound Images Based on an Evolutionary Scheme. Informatics 2014, 1, 52-71.

View more citation formats

Related Articles

Article Metrics


[Return to top]
Informatics EISSN 2227-9709 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert