DBPapers
DOI: 10.5593/sgem2011/s10.103

DEVELOPMENT OF METHODS FOR THE PROCESSING OF MEDICAL IMAGES USING GENETIC ALGORITHMS

AUTHOR/S: L. LICEV, T. FABIAN
Monday 1 August 2011 by Libadmin2011

11th International Multidisciplinary Scientific GeoConference SGEM2011, www.sgem.org, SGEM2011 Conference Proceedings/ ISSN 1314-2704, June 20-25, 2011, Vol. 2, 495-502 pp

ABSTRACT

In this paper we deal with analysis and evaluation of objects of interest which are
present in ultrasound images as well as assessment of the progress or regressions that
occurred in these objects. These objects are highly significant from a medicinal
perspective and include atherosclerostic plaque in carotid arteries, the intima-media
thickness in the distal part of the common carotid artery, cerebral cortex size and brain
stem findings in cases of Parkinson disease. Here, we describe procedures employing
combination of common methods and evolutionary algorithms for recognizing points of
interest in the images that may serve in determining various parameters and properties
of analyzed objects. We use the evolutionary algorithms to optimize the energy function
of deformable models used to approximate the locations and shapes of object boundaries in images. We suppose that evolutionary algorithms can be used to find the desired global solution. Evolutionary algorithms are based on principles of evolution found in nature and respect the Darwin`s theory of natural selection according to the
defined cost function and gene recombination and mutation. As the computation of gradient vector flow field and also the evolution of active contour are computationally very expensive, we investigate the suitability of the GPU for a parallel implementation.
In conclusion, we compare our approach with common numerical methods on real medical images segmentation.

Keywords: medical imaging, image segmentation, active contour, GVF snake, SOMA

PAPER 2011/s10.103: DEVELOPMENT OF METHODS FOR THE PROCESSING OF MEDICAL IMAGES USING GENETIC ALGORITHMS

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