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Contrast enhancement of medical images using a new version of the World Cup Optimization algorithm

  
@article{QIMS29674,
	author = {Yuanping Zhou and Changqin Shi and Bingyan Lai and Giorgos Jimenez},
	title = {Contrast enhancement of medical images using a new version of the World Cup Optimization algorithm},
	journal = {Quantitative Imaging in Medicine and Surgery},
	volume = {9},
	number = {9},
	year = {2019},
	keywords = {},
	abstract = {Background: In this paper, a new method for optimal enhancement of the contrast of a medical image is proposed. The main idea is to improve the Gamma correction method to enhance and highlight the image information and the details based on a new design of the World Cup Optimization (WCO) algorithm. Gamma correction is a suitable method for contrast enhancement with an efficiency that directly depends on the correct selection of the Gamma coefficient.
Methods: In this study, a newly presented algorithm was employed for optimal selection of the Gamma value by considering the entropy, edge content, and multi-objective optimization.
Results: The simulation results were compared with 5 state of the art methods for presenting method efficiency. To do this, contrast, homogeneity, weighted average peak signal-to-noise ratio (WPSNR), measure of enhancement (EME), and contrast-to-noise ratio (CNR) were employed.
Conclusions: Final results denote that the presented multi-objective optimization algorithm improves the quality of the image contrast and can provide more details and information than the other comparable methods.},
	url = {http://qims.amegroups.com/article/view/29674}
}