Husam Yahya¹, Dumitru Baleanu^2,3,4, Rabha W. Ibrahim^5,*, Nadia M.G. Al-Saidi⁶

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2531-2539, 2023, DOI:10.32604/cmc.2023.033282 - 31 October 2022

Abstract The current study provides a quantum calculus-based medical image enhancement technique that dynamically chooses the spatial distribution of image pixel intensity values. The technique focuses on boosting the edges and texture of an image while leaving the smooth areas alone. The brain Magnetic Resonance Imaging (MRI) scans are used to visualize the tumors that have spread throughout the brain in order to gain a better understanding of the stage of brain cancer. Accurately detecting brain cancer is a complex challenge that the medical system faces when diagnosing the disease. To solve this issue, this research… More >

Walid El-Shafai^1,2, Amira A. Mahmoud¹, Anas M. Ali^1,3, El-Sayed M. El-Rabaie¹, Taha E. Taha¹, Osama F. Zahran¹, Adel S. El-Fishawy¹, Naglaa F. Soliman⁴, Amel A. Alhussan^5,*, Fathi E. Abd El-Samie¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3795-3814, 2022, DOI:10.32604/cmc.2022.029134 - 16 June 2022

Abstract In the literature, numerous techniques have been employed to decrease noise in medical image modalities, including X-Ray (XR), Ultrasonic (Us), Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET). These techniques are organized into two main classes: the Multiple Image (MI) and the Single Image (SI) techniques. In the MI techniques, images usually obtained for the same area scanned from different points of view are used. A single image is used in the entire procedure in the SI techniques. SI denoising techniques can be carried out both in a transform or spatial… More >

Xi Chen¹, Yanpeng Wu^2,*, Chenxue Zhu², Hongjun Liu³

Journal of New Media, Vol.4, No.3, pp. 117-123, 2022, DOI:10.32604/jnm.2022.027060 - 13 June 2022

Abstract The Hessian matrix has a wide range of applications in image processing, such as edge detection, feature point detection, etc. This paper proposes an image enhancement algorithm based on the Hessian matrix. First, the Hessian matrix is obtained by convolving the derivative of the Gaussian function. Then use the Hessian matrix to enhance the linear structure in the image. Experimental results show that the method proposed in this paper has strong robustness and accuracy. More >

Ibtisam Aldawish¹, Hamid A. Jalab^2,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1307-1316, 2022, DOI:10.32604/cmc.2022.029445 - 18 May 2022

Abstract The lungs CT scan is used to visualize the spread of the disease across the lungs to obtain better knowledge of the state of the COVID-19 infection. Accurately diagnosing of COVID-19 disease is a complex challenge that medical system face during the pandemic time. To address this problem, this paper proposes a COVID-19 image enhancement based on Mittag-Leffler-Chebyshev polynomial as pre-processing step for COVID-19 detection and segmentation. The proposed approach comprises the Mittag-Leffler sum convoluted with Chebyshev polynomial. The idea for using the proposed image enhancement model is that it improves images with low gray-level… More >

Jingchun Zhou^1,*, Taian Shi¹, Weishi Zhang^1,*, Weishen Chu²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 1063-1081, 2022, DOI:10.32604/cmes.2022.019447 - 14 March 2022

Abstract The scattering and absorption of light propagating underwater cause the underwater images to present low contrast, color deviation, and loss of details, which in turn make human posture recognition challenging. To address these issues, this study introduced the dual-guided filtering technique and developed an underwater diver image improvement method. First, the color distortion of the underwater diver image was solved using white balance technology to obtain a color-corrected image. Second, dual-guided filtering was applied to the white balanced image to correct the distorted color and enhance its details. Four feature weight maps of the two More >

Zuozheng Lian¹, Hong Zhao^2,*, Qianjun Zhang¹, Haizhen Wang¹, E. Erdun³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1515-1528, 2022, DOI:10.32604/cmc.2022.024779 - 24 February 2022

Abstract For scanning electron microscopes with high resolution and a strong electric field, biomass materials under observation are prone to radiation damage from the electron beam. This results in blurred or non-viable images, which affect further observation of material microscopic morphology and characterization. Restoring blurred images to their original sharpness is still a challenging problem in image processing. Traditional methods can't effectively separate image context dependency and texture information, affect the effect of image enhancement and deblurring, and are prone to gradient disappearance during model training, resulting in great difficulty in model training. In this paper,… More >

Aymen Saad¹, Israa S. Kamil², Ahmed Alsayat³, Ahmed Elaraby^4,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 561-576, 2022, DOI:10.32604/cmc.2022.023878 - 24 February 2022

Abstract COVID-19 has been considered one of the recent epidemics that occurred at the last of 2019 and the beginning of 2020 that world widespread. This spread of COVID-19 requires a fast technique for diagnosis to make the appropriate decision for the treatment. X-ray images are one of the most classifiable images that are used widely in diagnosing patients’ data depending on radiographs due to their structures and tissues that could be classified. Convolutional Neural Networks (CNN) is the most accurate classification technique used to diagnose COVID-19 because of the ability to use a different number… More >

Rabha W. Ibrahim^1,*, Husam Yahya², Arkan J. Mohammed³, Nadia M. G. Al-Saidi⁴, Dumitru Baleanu^5,6,7

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 937-950, 2022, DOI:10.32604/iasc.2022.021954 - 17 November 2021

Abstract The interest in using fractal theory and its applications has grown in the field of image processing. Image enhancement is one of the feature processing tools, which aims to improve the details of an image. The enhancement of digital pictures is a challenging task due to the unforeseeable variation in the quality of the captured images. In this study, we present a mathematical model using a local conformable differential operator (LCDO). The proposed model is formulated by the theory of cantor fractal to generalize the definition of LCDO. The main advantage of utilizing LCDO for… More >

Hamid A. Jalab^1,*, Rabha W. Ibrahim², Ali M. Hasan³, Faten Khalid Karim⁴, Ala’a R. Al-Shamasneh¹, Dumitru Baleanu^5,6,7

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1467-1483, 2021, DOI:10.32604/cmc.2021.016047 - 13 April 2021

Abstract The enhancement of medical images is a challenging research task due to the unforeseeable variation in the quality of the captured images. The captured images may present with low contrast and low visibility, which might influence the accuracy of the diagnosis process. To overcome this problem, this paper presents a new fractional integral entropy (FITE) that estimates the unforeseeable probabilities of image pixels, posing as the main contribution of the paper. The proposed model dynamically enhances the image based on the image contents. The main advantage of FITE lies in its capability to enhance the… More >

Hamid A. Jalab¹, Ala’a R. Al-Shamasneh¹, Hadil Shaiba², Rabha W. Ibrahim^3,4,*, Dumitru Baleanu^5,6,7

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2061-2075, 2021, DOI:10.32604/cmc.2021.015170 - 05 February 2021

Abstract Recently, many rapid developments in digital medical imaging have made further contributions to health care systems. The segmentation of regions of interest in medical images plays a vital role in assisting doctors with their medical diagnoses. Many factors like image contrast and quality affect the result of image segmentation. Due to that, image contrast remains a challenging problem for image segmentation. This study presents a new image enhancement model based on fractional Rényi entropy for the segmentation of kidney MRI scans. The proposed work consists of two stages: enhancement by fractional Rényi entropy, and MRI… More >