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

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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.

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Zhou, Y., Shi, C., Lai, B., & Jimenez, G. (2019). Contrast enhancement of medical images using a new version of the World Cup Optimization algorithm. Quantitative Imaging in Medicine and Surgery, 9(9), 1528–1547. https://doi.org/10.21037/qims.2019.08.19

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