DocumentCode :
3006918
Title :
An Improved Algorithm for Medical Image Segmentation
Author :
Huang, Ting-Lei ; Bai, Xue
Author_Institution :
Guilin Univ. of Electron. Technol., Guilin
fYear :
2008
fDate :
25-26 Sept. 2008
Firstpage :
289
Lastpage :
292
Abstract :
The main objective of medical image segmentation is to extract and characterize anatomical structures with respect to some input features or expert knowledge. Traditional two-dimensional Otsu method for medical image segmentation is time-consuming computation and become an obstacle in real time application systems. This paper describes a way of medical image segmentation using optimized two-dimensional Otsu method based on improved genetic algorithm (GA). In proposed algorithm, the probability-ties of crossover are adaptively varied depending on the ranking value of individuals instead of fitness, and dyadic mutation operator was presented to take the place of the traditional one. The experimental results show that the new optimized method dramatically reduces the operating time in medical image segmentation while ensures the final image segmentation quality.
Keywords :
feature extraction; genetic algorithms; image segmentation; medical image processing; anatomical structure extraction; dyadic mutation operator; genetic algorithm; medical image segmentation; optimized 2D Otsu method; Anatomical structure; Background noise; Biomedical imaging; Clustering algorithms; Genetics; Histograms; Image segmentation; Optimization methods; Real time systems; Two dimensional displays; Medical Image Segmentation; Otsu method; improved genetic algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Genetic and Evolutionary Computing, 2008. WGEC '08. Second International Conference on
Conference_Location :
Hubei
Print_ISBN :
978-0-7695-3334-6
Type :
conf
DOI :
10.1109/WGEC.2008.116
Filename :
4637447
Link To Document :
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