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Search Results (9)
  • Open Access

    ARTICLE

    Blueberry anthocyanins extract attenuates oxidative stress and angiogenesis on an in vitro high glucose-induced retinopathy model through the miR-33/GLCCI1 axis

    WENBIN LUO1, YULING ZOU2, HONGXI WU3, ZHONGYI YANG1, ZHIPENG YOU2,*

    BIOCELL, Vol.48, No.8, pp. 1275-1284, 2024, DOI:10.32604/biocell.2024.051045 - 02 August 2024

    Abstract Background: Diabetes retinopathy (DR) is a complication of diabetes that affects patients’ vision. Previous studies have found blueberry anthocyanins extract (BAE) can inhibit the progression of DR, but its mechanism is not completely clear. Methods: To study the role of BAE in diabetes retinopathy, we treated human retinal endothelial cells (HRCECs) with 30 mM high glucose to simulate the microenvironment of diabetes retinopathy and used BAE to intervene the in vitro high glucose-induced retinopathy model. HRCEC cell viability and apoptosis rates were examined by Cell Counting Kit 8 (CCK-8) assay and flow cytometry assay. The binding… More >

  • Open Access

    ARTICLE

    EMU-Net: Automatic Brain Tumor Segmentation and Classification Using Efficient Modified U-Net

    Mohammed Aly1,*, Abdullah Shawan Alotaibi2

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 557-582, 2023, DOI:10.32604/cmc.2023.042493 - 31 October 2023

    Abstract Tumor segmentation is a valuable tool for gaining insights into tumors and improving treatment outcomes. Manual segmentation is crucial but time-consuming. Deep learning methods have emerged as key players in automating brain tumor segmentation. In this paper, we propose an efficient modified U-Net architecture, called EMU-Net, which is applied to the BraTS 2020 dataset. Our approach is organized into two distinct phases: classification and segmentation. In this study, our proposed approach encompasses the utilization of the gray-level co-occurrence matrix (GLCM) as the feature extraction algorithm, convolutional neural networks (CNNs) as the classification algorithm, and the… More >

  • Open Access

    ARTICLE

    Plant Leaf Diseases Classification Using Improved K-Means Clustering and SVM Algorithm for Segmentation

    Mona Jamjoom1, Ahmed Elhadad2, Hussein Abulkasim3,*, Safia Abbas4

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 367-382, 2023, DOI:10.32604/cmc.2023.037310 - 08 June 2023

    Abstract Several pests feed on leaves, stems, bases, and the entire plant, causing plant illnesses. As a result, it is vital to identify and eliminate the disease before causing any damage to plants. Manually detecting plant disease and treating it is pretty challenging in this period. Image processing is employed to detect plant disease since it requires much effort and an extended processing period. The main goal of this study is to discover the disease that affects the plants by creating an image processing system that can recognize and classify four different forms of plant diseases, More >

  • Open Access

    ARTICLE

    Smart Lung Tumor Prediction Using Dual Graph Convolutional Neural Network

    Abdalla Alameen*

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 369-383, 2023, DOI:10.32604/iasc.2023.031039 - 29 September 2022

    Abstract A significant advantage of medical image processing is that it allows non-invasive exploration of internal anatomy in great detail. It is possible to create and study 3D models of anatomical structures to improve treatment outcomes, develop more effective medical devices, or arrive at a more accurate diagnosis. This paper aims to present a fused evolutionary algorithm that takes advantage of both whale optimization and bacterial foraging optimization to optimize feature extraction. The classification process was conducted with the aid of a convolutional neural network (CNN) with dual graphs. Evaluation of the performance of the fused… More >

  • Open Access

    ARTICLE

    An Efficient Deep Learning-based Content-based Image Retrieval Framework

    M. Sivakumar1,*, N. M. Saravana Kumar2, N. Karthikeyan1

    Computer Systems Science and Engineering, Vol.43, No.2, pp. 683-700, 2022, DOI:10.32604/csse.2022.021459 - 20 April 2022

    Abstract The use of massive image databases has increased drastically over the few years due to evolution of multimedia technology. Image retrieval has become one of the vital tools in image processing applications. Content-Based Image Retrieval (CBIR) has been widely used in varied applications. But, the results produced by the usage of a single image feature are not satisfactory. So, multiple image features are used very often for attaining better results. But, fast and effective searching for relevant images from a database becomes a challenging task. In the previous existing system, the CBIR has used the… More >

  • Open Access

    ARTICLE

    Design of Logically Obfuscated Memory and Arithmetic Logic Unit for Improved Hardware Security

    M. Usharani1,*, B. Sakthivel2, K. Jayaram3, R. Renugadevi4

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1665-1675, 2022, DOI:10.32604/iasc.2022.023284 - 24 March 2022

    Abstract In any kind of digital system, the processor and memories are used to play a vital role in today’s trend. The processors and memories are done many critical tasks in the system. Whereas the processor used to do several functions and memories used to store and retrieve the data. But these processors and memories are more vulnerable to various hardware attacks. By using several new devices may lead to many security issues which the attackers can leverage to introduce a new hardware attack. Various hardware security (HS) studies have been presented to prevent hardware from… More >

  • Open Access

    ARTICLE

    A Lightweight Approach for Skin Lesion Detection Through Optimal Features Fusion

    Khadija Manzoor1, Fiaz Majeed2, Ansar Siddique2, Talha Meraj3, Hafiz Tayyab Rauf4,*, Mohammed A. El-Meligy5, Mohamed Sharaf6, Abd Elatty E. Abd Elgawad6

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1617-1630, 2022, DOI:10.32604/cmc.2022.018621 - 07 September 2021

    Abstract Skin diseases effectively influence all parts of life. Early and accurate detection of skin cancer is necessary to avoid significant loss. The manual detection of skin diseases by dermatologists leads to misclassification due to the same intensity and color levels. Therefore, an automated system to identify these skin diseases is required. Few studies on skin disease classification using different techniques have been found. However, previous techniques failed to identify multi-class skin disease images due to their similar appearance. In the proposed study, a computer-aided framework for automatic skin disease detection is presented. In the proposed… More >

  • Open Access

    ARTICLE

    Cervical Diseases Prediction Using LHVR Techniques

    Praveena Rajasekaran*, Preetha Jaganathan, Anjali Annadurai

    Computer Systems Science and Engineering, Vol.36, No.3, pp. 477-484, 2021, DOI:10.32604/csse.2021.014247 - 18 January 2021

    Abstract The stabilizing mechanisms of cervical spine spondylosis are involved in the degenerating segmentation vertebra, which often causes pain. Health of the individual is affected, both physically and mentally. Due to depression, nervousness, and psychological damages occur thereby losing their human activity functions. The nucleus pulposus of spinal disc herniation is prolapsed through a deficiency of annulus fibrosus. A jelly-like core part of the disc contains proteins that cause the tissues to become swollen when it touches the nucleus pulposus. The proposed Gradient Linear Classification (GLC) algorithm is used for the efficient automatic classification of disc More >

  • Open Access

    ARTICLE

    A GLCM-Feature-Based Approach for Reversible Image Transformation

    Xianyi Chen1,2,*, Haidong Zhong1,2, Zhifeng Bao3

    CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 239-255, 2019, DOI:10.32604/cmc.2019.03572

    Abstract Recently, a reversible image transformation (RIT) technology that transforms a secret image to a freely-selected target image is proposed. It not only can generate a stego-image that looks similar to the target image, but also can recover the secret image without any loss. It also has been proved to be very useful in image content protection and reversible data hiding in encrypted images. However, the standard deviation (SD) is selected as the only feature during the matching of the secret and target image blocks in RIT methods, the matching result is not so good and… More >

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