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Multilevel segmentation of 2D and volumetric medical images using hybrid Coronavirus Optimization Algorithm
Faculty
Computer Science
Year:
2022
Type of Publication:
ZU Hosted
Pages:
Authors:
Khalied Mohamed Hosny
Staff Zu Site
Abstract In Staff Site
Journal:
Computers in Biology and Medicine Elsevier Ltd
Volume:
Keywords :
Multilevel segmentation , , , volumetric medical images using
Abstract:
Medical image segmentation is a crucial step in Computer-Aided Diagnosis systems, where accurate segmentation is vital for perfect disease diagnoses. This paper proposes a multilevel thresholding technique for 2D and 3D medical image segmentation using Otsu and Kapur's entropy methods as fitness functions to determine the optimum threshold values. The proposed algorithm applies the hybridization concept between the recent Coronavirus Optimization Algorithm (COVIDOA) and Harris Hawks Optimization Algorithm (HHOA) to benefit from both algorithms' strengths and overcome their limitations. The improved performance of the proposed algorithm over COVIDOA and HHOA algorithms is demonstrated by solving 5 test problems from IEEE CEC 2019 benchmark problems. Medical image segmentation is tested using two groups of images, including 2D medical images and volumetric (3D) medical images, to demonstrate its superior performance. The utilized test images are from different modalities such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and X-ray images. The proposed algorithm is compared with seven well-known metaheuristic algorithms, where the performance is evaluated using four different metrics, including the best fitness values, Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Normalized Correlation Coefficient (NCC). The experimental results demonstrate the superior performance of the proposed algorithm in terms of convergence to the global optimum and making a good balance between exploration and exploitation properties. Moreover, the quality of the segmented images using the proposed algorithm at different threshold levels is better than the other methods according to PSNR, SSIM, and NCC values. Additionally, the Wilcoxon rank-sum test is conducted to prove the statistical significance of the proposed algorithm.
Author Related Publications
Khalied Mohamed Hosny, "SEMANTIC REPRESENTATION OF MUSIC DATABASE USING NEW ONTOLOGY-BASED SYSTEM", Journal of Theoretical and Applied Information Technology, 2020
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Khalied Mohamed Hosny, "Building a New Semantic Social Network Using Semantic Web-Based Techniques", ِASPG, 2021
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Khalied Mohamed Hosny, "New Graphical Ultimate Processor for Mapping Relational Database to Resource Description Framework", IEEE, 2022
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Khalied Mohamed Hosny, "Fast computation of accurate Zernike moments", Springer, 2008
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Khalied Mohamed Hosny, "Accurate Computation of QPCET for Color Images in Different Coordinate Systems", SPIE, 2017
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Department Related Publications
Walid Ibrahim Ibrahim Khedr, "Ad-hoc on Demand Authentication Chain Protocol - An Authentication Protocol for Ad-Hoc Networks", Institute for Systems and Technologies of Information, Control and Communication, 2015
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Khalied Mohamed Hosny, "Robust Color Image Hashing Using Quaternion Polar Complex Exponential Transform for Image Authentication", Springer, 2018
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Ehab Roshdy Mohamed, "Efficient compression of volumetric medical images using Legendre moments and differential evolution", Springer, 2020
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Asmaa Mohamed Khalid Mohamed Abbas, "Efficient compression of volumetric medical images using Legendre moments and differential evolution", Springer, 2020
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Khalied Mohamed Hosny, "Efficient compression of volumetric medical images using Legendre moments and differential evolution", Springer, 2020
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