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Almusallam, Naif, Muradova, Vusala, Abotaleb, Mostafa, Makarovskikh, Tatiana, Alkattan, Hussein, Gamal Ahmed, Omar, Mohsin Mijwil, Maad. (1405). A U-Net framework using differential equations for enhanced computer vision in lung disease diagnosis. سامانه مدیریت نشریات علمی, 14(1), 374-391. doi: 10.22034/cmde.2024.64290.2905
Naif Almusallam; Vusala Muradova; Mostafa O Abotaleb; Tatiana Makarovskikh; Hussein Alkattan; Omar Gamal Ahmed; Maad Mohsin Mijwil. "A U-Net framework using differential equations for enhanced computer vision in lung disease diagnosis". سامانه مدیریت نشریات علمی, 14, 1, 1405, 374-391. doi: 10.22034/cmde.2024.64290.2905
Almusallam, Naif, Muradova, Vusala, Abotaleb, Mostafa, Makarovskikh, Tatiana, Alkattan, Hussein, Gamal Ahmed, Omar, Mohsin Mijwil, Maad. (1405). 'A U-Net framework using differential equations for enhanced computer vision in lung disease diagnosis', سامانه مدیریت نشریات علمی, 14(1), pp. 374-391. doi: 10.22034/cmde.2024.64290.2905
Almusallam, Naif, Muradova, Vusala, Abotaleb, Mostafa, Makarovskikh, Tatiana, Alkattan, Hussein, Gamal Ahmed, Omar, Mohsin Mijwil, Maad. A U-Net framework using differential equations for enhanced computer vision in lung disease diagnosis. سامانه مدیریت نشریات علمی, 1405; 14(1): 374-391. doi: 10.22034/cmde.2024.64290.2905

A U-Net framework using differential equations for enhanced computer vision in lung disease diagnosis

Computational Methods for Differential Equations
مقاله 26، دوره 14، شماره 1، فروردین 2026، صفحه 374-391    اصل مقاله (3.33 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22034/cmde.2024.64290.2905
نویسندگان
Naif Almusallam1؛ Vusala Muradova2؛ Mostafa O Abotaleb* 3؛ Tatiana Makarovskikh4؛ Hussein Alkattan4؛ Omar Gamal Ahmed5؛ Maad Mohsin Mijwil6
1Department of Management Information Systems (MIS)‎, ‎School of Business‎, ‎King Faisal University (KFU)‎, ‎Al-Ahsa 31982‎, ‎Saudi Arabia.
2Lankaran State University‎, ‎Lankaran‎, ‎Azerbaijan.
3Engineering School of Digital Technologies, Yugra State University, Khanty Mansiysk, 628012, Russia.
4Department of System Programming‎, ‎South Ural State University‎, ‎Chelyabinsk‎, ‎454080‎, ‎Russia.
5Department of Electric Drive‎, ‎Mechatronics and Electromechanics‎, ‎South Ural State University‎, ‎Chelyabinsk‎, ‎454080‎, ‎Russia.
6College of Administration and Economics, Al-Iraqia University, Baghdad, Iraq.
چکیده
This study presents a U-Net-based approach for the classification of lung diseases using chest X-ray images. The model effectively leverages its encoder-decoder architecture and skip connections to capture both high-level semantic features and detailed spatial information, crucial for medical image analysis. The U-Net model was trained and tested on a dataset of 3,475 X-ray images, representing three classes: Normal, Lung Opacity, and Viral Pneumonia. The model achieved strong performance, with a weighted F1 score of 0.9770 and Cohen’s Kappa of 0.9653, demonstrating its high accuracy in classifying lung diseases. These results confirm the suitability of U-Net for medical imaging tasks, particularly in detecting subtle abnormalities in chest X-ray images. However, the study also identifies challenges, including class imbalance in medical datasets and the computational demands of training large models like the U-Net. Future improvements could focus on enhancing generalizability and reducing computational complexity through advanced data augmentation, domain adaptation, and architectural optimizations. Overall, this research highlights the potential of U-Net for developing reliable and efficient automated diagnostic tools in healthcare.
کلیدواژه‌ها
U-Net؛ Lung disease classification؛ Chest X-ray؛ Deep learning؛ Medical image analysis؛ Convolutional neural networks
مراجع
  • [1] M. Abotaleb, Soft Computing-Based Generalized Least Deviation Method Algorithm for Modeling and Forecasting COVID-19 using Quasilinear Recurrence Equations, Iraqi Journal For Computer Science and Mathematics, 5(3) (2024), 441–472.
  • [2] M. Abotaleb and T. Makarovskikh, Advanced milk production modelling using high-order generalized least deviation method, Modeling Earth Systems and Environment, 10(6) (2024), 7019–7047.
  • [3] M. O. Abotaleb, Solving the optimizing parameters problem for non-linear datasets using the high-order general least deviations method (GLDM) algorithm, Computational Methods for Differential Equations, 13(3) (2025), 940–967.
  • [4] N. H. Ali, S. A. Mohammed, and J. Manafian, Study on the simplified MCH equation and the combined KdV– mKdV equations with solitary wave solutions, Partial Differential Equations in Applied Mathematics, 9 (2024), 100599.
  • [5] M. Badri, M. Alkhaili, H. Aldhaheri, G. Yang, M. Albahar, S. Yaaqeib, and A. Alrashdi, Determined to be resilient: Analysis of the well-being of people with disabilities (People of determination) in Abu Dhabi during the COVID-19 pandemic, International Journal of Innovative Research and Scientific Studies, 7(1) (2024), 189–201.
  • [6] J. Brahma, A. Islary, and S. Ray, Nutritional evaluation and GC–MS analysis of bioactive compounds present in methanol extracts of dried fruit pericarp of garcinia pedunculata Roxb, Journal of Food Technology Research, 11(2) (2024), 27–37.
  • [7] T. B. Chandra, K. Verma, B. K. Singh, D. Jain, and S. S. Netam, Coronavirus disease (COVID-19) detection in chest X-ray images using majority voting based classifier ensemble, Expert Systems with Applications, 165 (2021), 113909.
  • [8] H. Chen, A. Shahi, G. Singh, J. Manafian, B. Eslami, and N. A. Alkader, Behavior of analytical schemes with non-paraxial pulse propagation to the cubic–quintic nonlinear Helmholtz equation, Mathematics and Computers in Simulation, 220 (2024), 341–356.
  • [9] J. Cheng, J. Manafian, G. Singh, A. Yadav, N. Kumari, R. Sharma, B. Eslami, and N. A. Alkader, Interaction between soliton and periodic solutions and the stability analysis to the Gilson–Pickering equation by bilinear method and exp(-θ(α))-function approach arising plasma physics, Optical and Quantum Electronics, 56(6) (2024), 1071.
  • [10] G. Dooley and H. Lenihan, An assessment of time series methods in metal price forecasting, Resources Policy, 30(3) (2005), 208–217.
  • [11] A. Esen, B. Karaagac, N. M. Yagmurlu, Y. Ucar, and J. Manafian, A numerical approach to dispersion-dissipationreaction model: third order KdV-Burger-Fisher equation, Physica Scripta, 99(8) (2024), 085260.
  • [12] X. C. Gui, J. Manafian, G. Singh, B. Eslami, S. F. Mahmud, K. H. Mohmmed, and N. A. Alkader, Wave pulses’ physical properties in birefringent optical fibres containing two vector solitons with coupled fractional LPD equation with Kerr’s law nonlinearity, Optical and Quantum Electronics, 56(6) (2024), 913.
  • [13] Y. Guo, Y. Chen, J. Manafian, S. Malmir, K. H. Mahmoud, and A. S. Alsubaie, Exploring N-soliton solutions, multiple rogue wave and the linear superposition principle to the generalized Hirota Satsuma-Ito equation, Scientific Reports, 14(1) (2024), 26171.
  • [14] S. Guo, D. Kong, J. Manafian, K. H. Mahmoud, A. S. Alsubaie, N. Kumari, R. Sharma, and N. Ahmad, Modulational stability and multiple rogue wave solutions for a generalized (3+1)-D nonlinear wave equation in fluid with gas bubbles, Alexandria Engineering Journal, 106 (2024), 1–18.
  • [15] J. Y. Hesterman, L. Caucci, M. A. Kupinski, H. H. Barrett, and L. R. Furenlid, Maximum-likelihood estimation with a contracting-grid search algorithm, IEEE Transactions on Nuclear Science, 57(3) (2010), 1077–1084.
  • [16] A. L. A. Kassem, Snake Optimization with deep learning enabled disease detection model for colorectal cancer, Journal of Smart Internet of Things, 2022(1) (2023), 178–195.
  • [17] A. S. Khalifa, H. M. Ahmed, N. M. Badra, J. Manafian, K. H. Mahmoud, K. S. Nisar, and W. B. Rabie, Derivation of some solitary wave solutions for the (3+1)-dimensional pKP-BKP equation via the IME tanh function method, AIMS Mathematics, 9(10) (2024), 27704–27720.
  • [18] L. Lan, J. Manafian, B. Eslami, A. H. A. Hussein, K. H. Mahmoud, A. S. Alsubaie, A. G. Taki, and A. Hajar, Homoclinic and N-soliton solutions to variable-coefficient KP equation arising two-temperature ions in dusty plasma, Optical and Quantum Electronics, 56(7) (2024), 1223.
  • [19] Y. Li, J. Manafian, S. F. S. Takami, Z. M. Shatouri, F. A. Alenizi, A. H. Alawadi, and A. Alsaalamy, Study of the modulational instability and miscellaneous soliton for metamaterials via three powerful schemes, Journal of Nonlinear Optical Physics & Materials, (2023), 2350090.
  • [20] W. Li, Y. Kuang, J. Manafian, S. Malmir, B. Eslami, K. H. Mahmoud, and A. S. Alsubaie, Multiple rogue wave, double-periodic soliton and breather wave solutions for a generalized breaking soliton system in (3+1)-dimensions, Scientific Reports, 14(1) (2024), 19723.
  • [21] H. Liu, L. Wang, Y. Nan, F. Jin, Q. Wang, and J. Pu, SDFN: Segmentation-based deep fusion network for thoracic disease classification in chest X-ray images, Computerized Medical Imaging and Graphics, 75 (2019), 66–73.
  • [22] Y. Liu, J. Manafian, N. A. Alkader, and B. Eslami, On soliton solutions, periodic wave solutions, asymptotic analysis and interaction phenomena of the (3+1)-dimensional JM equation, Modern Physics Letters A, 38(34n35) (2023), 2350118.
  • [23] M. Liu, J. Manafian, G. Singh, A. S. Alsubaie, K. H. Mahmoud, and P. Mustafayeva, Wave profile, Paul-Painlev´e approaches and phase plane analysis to the generalized (3+1)-dimensional shallow water wave model, Qualitative Theory of Dynamical Systems, 23(1) (2024), 41.
  • [24] Y. Liu, J. Manafian, G. Singh, N. A. Alkader, and K. S. Nisar, Analytical investigations of propagation of ultrabroad nonparaxial pulses in a birefringent optical waveguide by three computational ideas, Scientific Reports, 14(1) (2024), 6317.
  • [25] J. Luo, J. Manafian, B. Eslami, K. H. Mahmoud, R. Sharma, N. Kumari, and A. Alsubaie, Assorted optical solitons of the (1+1)- and (2+1)-dimensional Chiral nonlinear Schrödinger equations using modified extended tanh-function technique, Scientific Reports, 14(1) (2024), 1–23.
  • [26] J. Manafian, W. R. Juadih, A. M. Rao, B. Eslami, N. Allahverdiyeva, and P. Mustafayeva, New Solitary Waves for Thin-Film Ferroelectric Material Equation Arising in Dielectric Materials, Acta Mechanica et Automatica, 18(3) (2024), 367–384.
  • [27] J. Manafian, L. A. Dawood, and M. Lakestani, New solutions to a generalized fifth-order KdV like equation with prime number p= 3 via a generalized bilinear differential operator, Partial Differential Equations in Applied Mathematics, 9 (2024), 100600.
  • [28] B. Pradhan, B. Boro, A. N. Dev, J. Manafian, and N. A. Alkader, Effect of ion anisotropy pressure in viscous plasmas: evolution of shock wave, Nonlinear Dynamics, 112(19) (2024), 17403–17416.
  • [29] B. Pradhan, B. Boro, M. K. Deka, A. N. Dev, J. Manafian, and N. A. Alkader, Effect of trapping of electrons and positrons on the evolution of shock wave in magnetized plasma: A complex trapped K-dV burgers’ equation, Results in Physics, 59 (2024), 107617.
  • [30] H. Qawaqneh, J. Manafian, M. Alharthi, and Y. Alrashedi, Stability Analysis, Modulation Instability, and BetaTime Fractional Exact Soliton Solutions to the Van der Waals Equation, Mathematics, 12(14) (2024), 2257.
  • [31] Y. Qi, J. Manafian, K. M. Sulieman, A. Kumar, N. Kumari, R. Sharma, M. Fazli, and T. Awad, Multi wave solutions and wave propagation in plasma physics over the Gilson-Pickering equation by modified extended tanhfunction method, Optical and Quantum Electronics, 56(6) (2024), 1008.
  • [32] X. Rao, J. Manafian, M. Gavahi, B. Eslami, M. K. Abdulameer, E. R. Alwaily, and Q. A. Qizi, Paul-Painlev´e Analysis, Soliton and Periodic Wave in the Fractional Thermophoretic Motion Equation via Graphene Sheets, Qualitative Theory of Dynamical Systems, 23(3) (2024), 136.
  • [33] O. Ronneberger, P. Fischer, and T. Brox, U-Net: Convolutional Networks for Biomedical Image Segmentation, Medical Image Computing and Computer-Assisted Intervention (MICCAI), 234 (2015), 234–241.
  • [34] C. Shorten and T. M. Khoshgoftaar, A survey on image data augmentation for deep learning, Journal of Big Data, 6(1) (2019), 1–48.
  • [35] S. Wen, J. Manafian, S. Sedighi, S. P. Atmaca, C. Gallegos, K. H. Mahmoud, and A. S. Alsubaie, Interactions among lump optical solitons for coupled nonlinear Schrödinger equation with variable coefficient via bilinear method, Scientific Reports, 14(1) (2024), 19568.
  • [36] X. Wu, J. Manafian, G. Singh, B. Eslami, A. Aldurayhim, N. A. Mohammad Ali Khalil, and A. Alawadi, Different lump k-soliton solutions to (2+1)-dimensional KdV system using Hirota binary Bell polynomials, Open Physics, 21(1) (2023), 20230167.
  • [37] Q. Yang, J. Manafian, K. H. Mahmoud, and A. Aldurayhim, Abundant exact traveling wave solutions and modulation instability analysis to the generalized Hirota–Satsuma–Ito equation, Open Physics, 22(1) (2024), 20240027.
  • [38] J. Zhang, J. Manafian, S. Raut, S. Roy, K. H. Mahmoud, and A. S. Alsubaie, Study of two soliton and shock wave structures by weighted residual method and Hirota bilinear approach, Nonlinear Dynamics, 112 (2024), 12375– 12391.
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