Directional mutation and crossover boosted ant colony optimization with application to COVID-19 X-ray image segmentation

Computers in Biology and Medicine, Journal Year: 2022, Volume and Issue: 148, P. 105810 - 105810

Published: July 13, 2022

Language: Английский

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Simulated annealing-based dynamic step shuffled frog leaping algorithm: Optimal performance design and feature selection

Neurocomputing, Journal Year: 2022, Volume and Issue: 503, P. 325 - 362

Published: June 28, 2022

Language: Английский

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Modified Remora Optimization Algorithm for Global Optimization and Multilevel Thresholding Image Segmentation

Mathematics, Journal Year: 2022, Volume and Issue: 10(7), P. 1014 - 1014

Published: March 22, 2022

Image segmentation is a key stage in image processing because it simplifies the representation of and facilitates subsequent analysis. The multi-level thresholding technique considered one most popular methods efficient straightforward. Many relative works use meta-heuristic algorithms (MAs) to determine threshold values, but they have issues such as poor convergence accuracy stagnation into local optimal solutions. Therefore, alleviate these shortcomings, this paper, we present modified remora optimization algorithm (MROA) for global tasks. We used Brownian motion promote exploration ability ROA provide greater opportunity find solution. Second, lens opposition-based learning introduced enhance search agents jump out To substantiate performance MROA, first 23 benchmark functions evaluate performance. compared with seven well-known regarding accuracy, speed, significant difference. Subsequently, tested quality MORA on eight grayscale images cross-entropy objective function. experimental metrics include peak signal-to-noise ratio (PSNR), structure similarity (SSIM), feature (FSIM). A series results proved that MROA has advantages among algorithms. Consequently, proposed promising method problems segmentation.

Language: Английский

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An adaptive quadratic interpolation and rounding mechanism sine cosine algorithm with application to constrained engineering optimization problems

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 213, P. 119041 - 119041

Published: Oct. 17, 2022

Language: Английский

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Gaussian kernel probability-driven slime mould algorithm with new movement mechanism for multi-level image segmentation

Measurement, Journal Year: 2022, Volume and Issue: 192, P. 110884 - 110884

Published: Feb. 14, 2022

Language: Английский

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A self-adaptive quantum equilibrium optimizer with artificial bee colony for feature selection

Computers in Biology and Medicine, Journal Year: 2023, Volume and Issue: 153, P. 106520 - 106520

Published: Jan. 2, 2023

Language: Английский

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Multi-level thresholding segmentation for pathological images: Optimal performance design of a new modified differential evolution

Computers in Biology and Medicine, Journal Year: 2022, Volume and Issue: 148, P. 105910 - 105910

Published: Aug. 5, 2022

Language: Английский

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Multi-verse Optimizer with Rosenbrock and Diffusion Mechanisms for Multilevel Threshold Image Segmentation from COVID-19 Chest X-Ray Images

Journal of Bionic Engineering, Journal Year: 2023, Volume and Issue: 20(3), P. 1198 - 1262

Published: Jan. 4, 2023

Language: Английский

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A convolutional neural network with pixel-wise sparse graph reasoning for COVID-19 lesion segmentation in CT images

Computers in Biology and Medicine, Journal Year: 2023, Volume and Issue: 155, P. 106698 - 106698

Published: Feb. 22, 2023

Language: Английский

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CNN-IKOA: convolutional neural network with improved Kepler optimization algorithm for image segmentation: experimental validation and numerical exploration

Journal Of Big Data, Journal Year: 2024, Volume and Issue: 11(1)

Published: Jan. 10, 2024

Abstract Chest diseases, especially COVID-19, have quickly spread throughout the world and caused many deaths. Finding a rapid accurate diagnostic tool was indispensable to combating these diseases. Therefore, scientists thought of combining chest X-ray (CXR) images with deep learning techniques rapidly detect people infected COVID-19 or any other disease. Image segmentation as preprocessing step has an essential role in improving performance techniques, it could separate most relevant features better train techniques. several approaches were proposed tackle image problem accurately. Among methods, multilevel thresholding-based methods won significant interest due their simplicity, accuracy, relatively low storage requirements. However, increasing threshold levels, traditional failed achieve segmented reasonable amount time. researchers recently used metaheuristic algorithms this problem, but existing still suffer from slow convergence speed stagnation into local minima number levels increases. study presents alternative technique based on enhanced version Kepler optimization algorithm (KOA), namely IKOA, segment CXR at small, medium, high levels. Ten are assess IKOA ten (T-5, T-7, T-8, T-10, T-12, T-15, T-18, T-20, T-25, T-30). To observe its effectiveness, is compared terms indicators. The experimental outcomes disclose superiority over all algorithms. Furthermore, IKOA-based eight different newly CNN model called CNN-IKOA find out effectiveness step. Five indicators, overall precision, recall, F1-score, specificity, CNN-IKOA’s effectiveness. CNN-IKOA, according outcomes, outstanding for where reach 94.88% 96.57% 95.40% recall.

Language: Английский

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