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  • Open Access

    ARTICLE

    A Novel Approach to Breast Tumor Detection: Enhanced Speckle Reduction and Hybrid Classification in Ultrasound Imaging

    K. Umapathi1,*, S. Shobana1, Anand Nayyar2, Judith Justin3, R. Vanithamani3, Miguel Villagómez Galindo4, Mushtaq Ahmad Ansari5, Hitesh Panchal6,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1875-1901, 2024, DOI:10.32604/cmc.2024.047961

    Abstract Breast cancer detection heavily relies on medical imaging, particularly ultrasound, for early diagnosis and effective treatment. This research addresses the challenges associated with computer-aided diagnosis (CAD) of breast cancer from ultrasound images. The primary challenge is accurately distinguishing between malignant and benign tumors, complicated by factors such as speckle noise, variable image quality, and the need for precise segmentation and classification. The main objective of the research paper is to develop an advanced methodology for breast ultrasound image classification, focusing on speckle noise reduction, precise segmentation, feature extraction, and machine learning-based classification. A unique approach is introduced that combines Enhanced… More >

  • Open Access

    ARTICLE

    An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

    Syed Ayaz Ali Shah1,*, Aamir Shahzad1,*, Musaed Alhussein2, Chuan Meng Goh3, Khursheed Aurangzeb2, Tong Boon Tang4, Muhammad Awais5

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2565-2583, 2024, DOI:10.32604/cmc.2024.047597

    Abstract Diagnosing various diseases such as glaucoma, age-related macular degeneration, cardiovascular conditions, and diabetic retinopathy involves segmenting retinal blood vessels. The task is particularly challenging when dealing with color fundus images due to issues like non-uniform illumination, low contrast, and variations in vessel appearance, especially in the presence of different pathologies. Furthermore, the speed of the retinal vessel segmentation system is of utmost importance. With the surge of now available big data, the speed of the algorithm becomes increasingly important, carrying almost equivalent weightage to the accuracy of the algorithm. To address these challenges, we present a novel approach for retinal… More > Graphic Abstract

    An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

  • Open Access

    ARTICLE

    Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

    Norah Abdullah Al-Johany1,*, Sanaa Abdullah Sharaf1,2, Fathy Elbouraey Eassa1,2, Reem Abdulaziz Alnanih1,2,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3139-3173, 2024, DOI:10.32604/cmc.2024.047392

    Abstract The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed memory systems. However, MPI implementations can contain defects that impact the reliability and performance of parallel applications. Detecting and correcting these defects is crucial, yet there is a lack of published models specifically designed for correcting MPI defects. To address this, we propose a model for detecting and correcting MPI defects (DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blocking point-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defects addressed by the DC_MPI model include illegal… More >

  • Open Access

    ARTICLE

    Enhanced Object Detection and Classification via Multi-Method Fusion

    Muhammad Waqas Ahmed1, Nouf Abdullah Almujally2, Abdulwahab Alazeb3, Asaad Algarni4, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3315-3331, 2024, DOI:10.32604/cmc.2024.046501

    Abstract Advances in machine vision systems have revolutionized applications such as autonomous driving, robotic navigation, and augmented reality. Despite substantial progress, challenges persist, including dynamic backgrounds, occlusion, and limited labeled data. To address these challenges, we introduce a comprehensive methodology to enhance image classification and object detection accuracy. The proposed approach involves the integration of multiple methods in a complementary way. The process commences with the application of Gaussian filters to mitigate the impact of noise interference. These images are then processed for segmentation using Fuzzy C-Means segmentation in parallel with saliency mapping techniques to find the most prominent regions. The… More >

  • Open Access

    ARTICLE

    Automatic Finding of Brain-Tumour Group Using CNN Segmentation and Moth-Flame-Algorithm, Selected Deep and Handcrafted Features

    Imad Saud Al Naimi1,2,*, Syed Alwee Aljunid Syed Junid1, Muhammad lmran Ahmad1,*, K. Suresh Manic2,3

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2585-2608, 2024, DOI:10.32604/cmc.2024.046461

    Abstract Augmentation of abnormal cells in the brain causes brain tumor (BT), and early screening and treatment will reduce its harshness in patients. BT’s clinical level screening is usually performed with Magnetic Resonance Imaging (MRI) due to its multi-modality nature. The overall aims of the study is to introduce, test and verify an advanced image processing technique with algorithms to automatically extract tumour sections from brain MRI scans, facilitating improved accuracy. The research intends to devise a reliable framework for detecting the BT region in the two-dimensional (2D) MRI slice, and identifying its class with improved accuracy. The methodology for the… More >

  • Open Access

    ARTICLE

    Harnessing ML and GIS for Seismic Vulnerability Assessment and Risk Prioritization

    Shalu1, Twinkle Acharya1, Dhwanilnath Gharekhan1,*, Dipak Samal2

    Revue Internationale de Géomatique, Vol.33, pp. 111-134, 2024, DOI:10.32604/rig.2024.051788

    Abstract Seismic vulnerability modeling plays a crucial role in seismic risk assessment, aiding decision-makers in pinpointing areas and structures most prone to earthquake damage. While machine learning (ML) algorithms and Geographic Information Systems (GIS) have emerged as promising tools for seismic vulnerability modeling, there remains a notable gap in comprehensive geospatial studies focused on India. Previous studies in seismic vulnerability modeling have primarily focused on specific regions or countries, often overlooking the unique challenges and characteristics of India. In this study, we introduce a novel approach to seismic vulnerability modeling, leveraging ML and GIS to address these gaps. Employing Artificial Neural… More >

  • Open Access

    ARTICLE

    MAPK9 as a therapeutic target: unveiling ferroptosis in localized prostate cancer progression

    CHENG-GONG LUO1,2,#, JIAO ZHANG1,#, YUN-ZHAO AN1, XUAN LIU1, SHUAI-JIE LI1, WEI ZHANG1, KAI LI1, XU ZHAO1, DONG-BO YUAN1, LING-YUE AN1, WEI CHEN2, YE TIAN1,*, BIN XU1,*

    BIOCELL, Vol.48, No.5, pp. 771-792, 2024, DOI:10.32604/biocell.2024.048878

    Abstract Background: Ferroptosis, a lipid peroxidation-mediated programmed cell death, is closely linked to tumor development, including prostate cancer (PCa). Despite established connections between ferroptosis and PCa, a comprehensive investigation is essential for understanding its impact on patient prognosis. Methods: A risk model incorporating four ferroptosis-related genes was developed and validated. Elevated risk scores correlated with an increased likelihood of biochemical recurrence (BCR), diminished immune infiltration, and adverse clinicopathological characteristics. To corroborate these results, we performed validation analyses utilizing datasets from both the Cancer Genome Atlas Cohort (TCGA) and the Gene Expression Synthesis Cohort (GEO). Moreover, we conducted further investigations into the… More >

  • Open Access

    ARTICLE

    Quercetin regulates depression-like behavior in CUMS rat models via TLR4/NF-κB signaling

    YUANYUAN LI1, BITAO ZHANG1, ZILONG CUI1, PEIJIAN FAN1, SHAOXIAN WANG1,2,*

    BIOCELL, Vol.48, No.5, pp. 731-744, 2024, DOI:10.32604/biocell.2024.048820

    Abstract Background: Depression is becoming increasingly prevalent around the world, imposing a substantial burden on individuals, families, as well as society. Quercetin is known to be highly effective in treating depression. However, additional research is needed to dissect the mechanisms of its anti-depressive effects. Methods: For this study, Sprague-Dawley (SD) rats were randomized into the control, model, quercetin, or fluoxetine group. The latter three groups were exposed to chronic unpredictable mild stress (CUMS) for 42 d. The first two groups received saline solution daily via oral gavage. Meanwhile, the quercetin group was orally administered a quercetin suspension (52.08 mg/kg) every day,… More >

  • Open Access

    ARTICLE

    Galectin 2 regulates JAK/STAT3 signaling activity to modulate oral squamous cell carcinoma proliferation and migration in vitro

    XINRU FENG1, LI XIAO2,*

    BIOCELL, Vol.48, No.5, pp. 793-801, 2024, DOI:10.32604/biocell.2024.048395

    Abstract Background: Galectin 2 (LGALS2) is a protein previously reported to serve as a mediator of disease progression in a range of cancers. The function of LGALS2 in oral squamous cell carcinoma (OSCC), however, has yet to be explored, prompting the present study to address this literature gap. Methods: Overall, 144 paired malignant tumor tissues and paracancerous OSCC patient samples were harvested and the LGALS2 expression levels were examined through qPCR and western immunoblotting. The LGALS2 coding sequence was introduced into the pcDNA3.0 vector, to enable the overexpression of this gene, while an LGALS2-specific shRNA and corresponding controls were also obtained.… More >

  • Open Access

    ARTICLE

    Bioinformatics comprehensive analysis confirmed the potential involvement of SLC22A1 in lower-grade glioma progression and prognosis

    JING HUI1,2, NANA SUN3, YONG LIU4, CHUNBO YU1,2, YONG KE4, YONG CAO4, ANXIAO YU4, QINGHONG KONG1,2,*, YUN LIU1,2,4,*

    BIOCELL, Vol.48, No.5, pp. 803-815, 2024, DOI:10.32604/biocell.2024.047122

    Abstract Background: Although it has been established that the human Solute Carrier Family 22 (SLC22) functions as a cationic transporter, influencing cellular biological metabolism by modulating the uptake of various cations, its impact on cancer prognosis remains unclear. Methods: We conducted a comprehensive analysis utilizing data from The Cancer Genome Atlas (TCGA) and other databases to assess the prognostic value and functional implications across various tumors. Silence of SLC22A1 RNA in glioma U251 cells was performed to access the impact of SLC22A1 on lower-grade glioma (LGG) progression. Results: Our findings demonstrated a significant correlation between SLC22A1 expression and the survival time… More >

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