Adaptation of Region Growing thresholds using Memetic Programming algorithm

This paper presents a new strategy for the segmentation of brain images from the volumetric Magnetic Resonance Imaging (MRI). We propose a new segmentation technique that hybridize an evolutionary algorithm, called the Memetic Programming (MP) algorithm, with the Region Growing (RG) technique. The M...

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Vydáno v:2013 IEEE/ACIS 12th International Conference on Computer and Information Science (ICIS 2013) : Niigata, Japan, 16-20 June 2013 s. 29 - 34
Hlavní autoři: Ayman, Ahmed, Mabrouk, Emad, Elnomery, Zanaty
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.06.2013
Témata:
Automatic Threshold
Biomedical imaging
Brain MRI
Image segmentation
Magnetic resonance imaging
Medical Image Segmentation
Memetic Programming
Noise
Radio frequency
Region Growing
Sociology
Statistics
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Shrnutí:This paper presents a new strategy for the segmentation of brain images from the volumetric Magnetic Resonance Imaging (MRI). We propose a new segmentation technique that hybridize an evolutionary algorithm, called the Memetic Programming (MP) algorithm, with the Region Growing (RG) technique. The MP algorithm generates new threshold functions and then the RG uses these thresholds to perform an efficient segmentation of MRI images. The proposed segmentation technique are tested through a set of medical images with different noise and Radio Frequency (RF) levels. The experimental results show that the proposed technique produces more accurate and promising results.
DOI:10.1109/ICIS.2013.6607812