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