ICTACT Journal on Image and Video Processing

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Enhancing the Medical Images Quality Using Adaptive Genetic Algorithm


Affiliations
1 Department Artificial Intelligence and Data Science, Rajalakshmi Institute of Technology, India
2 Department of Electrical and Electronics Engineering, B.S.Abdur Rahman Crescent Institute of Science and Technology, India
3 Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, India
     

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It is obvious that there is a need for a Medical Decisiveness Determine System (MDDS) should be able to diagnose abnormalities in medical imaging. This is because the medical diagnosis system in health care sectors requires assistants to serve as secondary opinions for medical practitioners. During the process of picture acquisition, it is common practice to adjust the contrast level of medical images in order to prevent image degradation. Contrast enhancement in medical images is typically seen as an optimisation problem, and the Adaptive Genetic Algorithm (AGA) algorithm is utilised in order to arrive at the best possible answer. The findings of the comparison are established between the Adaptive Genetic Algorithm that has been proposed and other algorithms that are already in existence. A number of different performance indicators, including PSNR, SSIM, MSSIM, IFC, VIF, VSNR, MSE, SDME, and NAE, are utilised in order to make comparisons between the results. Methods that have been developed and those that already exist are evaluated using a variety of cancer pictures. As a result, the contrast and quality of medical images can be improved through the utilisation of AGA, which also offers a higher contrast level of medical images, hence facilitating improved decision-making by medical professionals.

Keywords

MDDS, AGA, SDME, Medical Images.
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  • Enhancing the Medical Images Quality Using Adaptive Genetic Algorithm

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Authors

C. Srivenkateswaran
Department Artificial Intelligence and Data Science, Rajalakshmi Institute of Technology, India
K. Regin Bose
Department Artificial Intelligence and Data Science, Rajalakshmi Institute of Technology, India
Belwin J. Brearley
Department of Electrical and Electronics Engineering, B.S.Abdur Rahman Crescent Institute of Science and Technology, India
D.C. Jullie Josephine
Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, India

Abstract


It is obvious that there is a need for a Medical Decisiveness Determine System (MDDS) should be able to diagnose abnormalities in medical imaging. This is because the medical diagnosis system in health care sectors requires assistants to serve as secondary opinions for medical practitioners. During the process of picture acquisition, it is common practice to adjust the contrast level of medical images in order to prevent image degradation. Contrast enhancement in medical images is typically seen as an optimisation problem, and the Adaptive Genetic Algorithm (AGA) algorithm is utilised in order to arrive at the best possible answer. The findings of the comparison are established between the Adaptive Genetic Algorithm that has been proposed and other algorithms that are already in existence. A number of different performance indicators, including PSNR, SSIM, MSSIM, IFC, VIF, VSNR, MSE, SDME, and NAE, are utilised in order to make comparisons between the results. Methods that have been developed and those that already exist are evaluated using a variety of cancer pictures. As a result, the contrast and quality of medical images can be improved through the utilisation of AGA, which also offers a higher contrast level of medical images, hence facilitating improved decision-making by medical professionals.

Keywords


MDDS, AGA, SDME, Medical Images.

References