Segmentation of Brain Tumor Images Using Genetic Algorithms

Nathem, Mohameed; Kashmola, Manar Y.; Abdullah, Dhuha Basheer

doi:10.33899/csmj.2009.163783

	Segmentation of Brain Tumor Images Using Genetic Algorithms
AL-Rafidain Journal of Computer Sciences and Mathematics
Article 21, Volume 6, Issue 1, 2009, Pages 31-45 PDF (820.19 K)
Document Type: Research Paper
DOI: 10.33899/csmj.2009.163783
Authors
Mohameed Nathem¹; Manar Y. Kashmola¹; Dhuha Basheer Abdullah²
¹College of Computer Sciences and Mathematics University of Mosul, Iraq
²College of Computer Sciences and Mathematics University of Mosul, Iraq
Abstract
In this research, the brain images resulting from computerized tomography (CT) have been used in order to determine the tumor area in the brain. the steps started by preprocessing operation to the image before inputting it to algorithm .the image was converted to binary image in order to segment the image, later on into equal segments ,then the correlation coefficient was found among these segments ,these values used as fitness function in the genetic algorithm in order to different iate between segments ,the result of the genetic algorithm was segment numbers which will be merged to form the sub-images ,then continuing these steps till determining the tumor approximate location. Another approach of image segmentation has been used without using the genetic algorithm by choosing the segments though a certain condition not randomly. Satisfying results have been reached in both approaches, but in different execution times. In both approaches tumor location was determined approximately, as a result the genetic algorithm was succeeded in about 85% while the first algorithm determine 80% of tumor locations.
Keywords
CT; brain; genetic algorithm; Segmentation

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