DocumentCode :
3155060
Title :
Adaptation of Region Growing thresholds using Memetic Programming algorithm
Author :
Ayman, Ahmed ; Mabrouk, Emad ; Elnomery, Zanaty
Author_Institution :
Fac. of Sci., Al-Azhar Univ., Assiut, Egypt
fYear :
2013
fDate :
16-20 June 2013
Firstpage :
29
Lastpage :
34
Abstract :
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.
Keywords :
biomedical MRI; brain; evolutionary computation; image segmentation; medical image processing; MP algorithm; MRI; RG technique; brain image segmentation; evolutionary algorithm; memetic programming algorithm; radio frequency; region growing threshold adaptation; volumetric magnetic resonance imaging; Biomedical imaging; Image segmentation; Magnetic resonance imaging; Noise; Radio frequency; Sociology; Statistics; Automatic Threshold; Brain MRI; Medical Image Segmentation; Memetic Programming; Region Growing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Information Science (ICIS), 2013 IEEE/ACIS 12th International Conference on
Conference_Location :
Niigata
Type :
conf
DOI :
10.1109/ICIS.2013.6607812
Filename :
6607812
Link To Document :
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