Hybrid Simulated Annealing-Evaporation Rate-Based Water Cycle Algorithm Application for Medical Image Enhancement
Visualizing medical images is difficult due to artifacts, poor local contrast, low soft tissue contrast, excessive noise levels, and a wide dynamic range. This has created a serious problem for physicians, resulting in unapproachable and inaccurate disease diagnoses. To circumvent this problem, this...
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Wiley
2024-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2024/3328299 |
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| author | Eyob Mersha Woldamanuel |
| author_facet | Eyob Mersha Woldamanuel |
| author_sort | Eyob Mersha Woldamanuel |
| collection | DOAJ |
| description | Visualizing medical images is difficult due to artifacts, poor local contrast, low soft tissue contrast, excessive noise levels, and a wide dynamic range. This has created a serious problem for physicians, resulting in unapproachable and inaccurate disease diagnoses. To circumvent this problem, this research proposes a medical image enhancement (MIE) approach based on the hybrid simulated annealing-evaporation rate-based water cycle algorithm (SA-ERWCA). The ERWCA enhances distorted medical images by finding the best optimal solution for the transformation parameters according to the fitness function. The fitness function consists of three objective measurements, namely, entropy, number of edges, and sum of edge intensities. Due to its high potential for finding a globally optimal solution, SA is applied solely to determine the optimized initial population of the ERWCA, thereby enhancing its convergence characteristics. To simply put, the main objective of SA is to avoid premature convergence of the ERWCA. Thus, blending SA and ERWCA produces better-quality medical images. The performance of the proposed algorithm was compared to histogram equalization (HE), low contrast stretching (LCS), contrast-limited adaptive histogram equalization (CLAHE), particle swarm optimization (PSO), accelerated PSO (APSO), and the water cycle algorithm (WCA). Along with the objective function fitness, seven full reference (FR) image quality assessment (IQA) metrics were implemented to evaluate image quality and compare performance. The findings of the present study showed that the proposed strategy outperforms all of the compared methods in terms of objective function fitness and perceptual visual IQA metrics such as the Harr wavelet-based perceptual similarity index (HaarPSI), visual signal-to-noise ratio (VSNR), and information content weighted structural similarity index measure (IW-SSIM). The suggested technique also exhibited better stability and faster convergence time to the optimum solution. Furthermore, the proposed approach outperformed others by avoiding premature convergence to the best solution and providing excellent optimization results with acceptable computational efficiency. |
| format | Article |
| id | doaj-art-7e36e8139fdb40c7a6180ff17dc1214d |
| institution | Kabale University |
| issn | 2090-0155 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
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| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-7e36e8139fdb40c7a6180ff17dc1214d2025-02-03T09:55:37ZengWileyJournal of Electrical and Computer Engineering2090-01552024-01-01202410.1155/2024/3328299Hybrid Simulated Annealing-Evaporation Rate-Based Water Cycle Algorithm Application for Medical Image EnhancementEyob Mersha Woldamanuel0School of Electrical and Computer EngineeringVisualizing medical images is difficult due to artifacts, poor local contrast, low soft tissue contrast, excessive noise levels, and a wide dynamic range. This has created a serious problem for physicians, resulting in unapproachable and inaccurate disease diagnoses. To circumvent this problem, this research proposes a medical image enhancement (MIE) approach based on the hybrid simulated annealing-evaporation rate-based water cycle algorithm (SA-ERWCA). The ERWCA enhances distorted medical images by finding the best optimal solution for the transformation parameters according to the fitness function. The fitness function consists of three objective measurements, namely, entropy, number of edges, and sum of edge intensities. Due to its high potential for finding a globally optimal solution, SA is applied solely to determine the optimized initial population of the ERWCA, thereby enhancing its convergence characteristics. To simply put, the main objective of SA is to avoid premature convergence of the ERWCA. Thus, blending SA and ERWCA produces better-quality medical images. The performance of the proposed algorithm was compared to histogram equalization (HE), low contrast stretching (LCS), contrast-limited adaptive histogram equalization (CLAHE), particle swarm optimization (PSO), accelerated PSO (APSO), and the water cycle algorithm (WCA). Along with the objective function fitness, seven full reference (FR) image quality assessment (IQA) metrics were implemented to evaluate image quality and compare performance. The findings of the present study showed that the proposed strategy outperforms all of the compared methods in terms of objective function fitness and perceptual visual IQA metrics such as the Harr wavelet-based perceptual similarity index (HaarPSI), visual signal-to-noise ratio (VSNR), and information content weighted structural similarity index measure (IW-SSIM). The suggested technique also exhibited better stability and faster convergence time to the optimum solution. Furthermore, the proposed approach outperformed others by avoiding premature convergence to the best solution and providing excellent optimization results with acceptable computational efficiency.http://dx.doi.org/10.1155/2024/3328299 |
| spellingShingle | Eyob Mersha Woldamanuel Hybrid Simulated Annealing-Evaporation Rate-Based Water Cycle Algorithm Application for Medical Image Enhancement Journal of Electrical and Computer Engineering |
| title | Hybrid Simulated Annealing-Evaporation Rate-Based Water Cycle Algorithm Application for Medical Image Enhancement |
| title_full | Hybrid Simulated Annealing-Evaporation Rate-Based Water Cycle Algorithm Application for Medical Image Enhancement |
| title_fullStr | Hybrid Simulated Annealing-Evaporation Rate-Based Water Cycle Algorithm Application for Medical Image Enhancement |
| title_full_unstemmed | Hybrid Simulated Annealing-Evaporation Rate-Based Water Cycle Algorithm Application for Medical Image Enhancement |
| title_short | Hybrid Simulated Annealing-Evaporation Rate-Based Water Cycle Algorithm Application for Medical Image Enhancement |
| title_sort | hybrid simulated annealing evaporation rate based water cycle algorithm application for medical image enhancement |
| url | http://dx.doi.org/10.1155/2024/3328299 |
| work_keys_str_mv | AT eyobmershawoldamanuel hybridsimulatedannealingevaporationratebasedwatercyclealgorithmapplicationformedicalimageenhancement |