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Informatics 2014, 1(1), 52-71; doi:10.3390/informatics1010052
Article

Artery Segmentation in Ultrasound Images Based on an Evolutionary Scheme

1,* , 2
 and 1
Received: 22 November 2013; in revised form: 16 January 2014 / Accepted: 6 February 2014 / Published: 25 February 2014
(This article belongs to the Special Issue Biomedical Imaging and Visualization)
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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.
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 which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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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.

AMA Style

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

Chicago/Turabian Style

Guzman, Pablo; Ros, Rafael; Ros, Eduardo. 2014. "Artery Segmentation in Ultrasound Images Based on an Evolutionary Scheme." Informatics 1, no. 1: 52-71.

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