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Research ArticleOpen accessAll words, across the recordEnhancing Brain MR Image Quality Using CNN With Best Denoising Modality for Improved Diagnosis of Abnormality: An AppraisalKavery Verma, Subodh Srivastava, Ritesh Kumar MishraDigital medical images acquired from the brain are highly susceptible to noise, which causes significant challenges for radiologists to identify abnormalities in a precise manner. Noise interference hampers both diagnostic accuracy and the interpretation of underlying abnormalities, potentially leading to flaw conclusions. Magnetic Resonance (MR) imaging is the most preferred digital imaging technique for brain abnormality detection. To achieve precise … …Journal of Computer Science, Vol. 22, Issue 3 · 26 Mar 2026 · 1,462 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Vertical Stacking-Based Ensemble Deep Learning Model for Early Diagnosis of Alzheimer's Disease Using Multimodal MRI ScansParvatham Niranjan Kumar, Lakshmana Phaneendra MaguluriEarly detection of Alzheimer's Disease (AD) is crucial for timely interventions that can slow disease progression, enhance quality of life, and assist with future planning. Convolutional Neural Networks (CNNs) are an efficient method for processing image-based data. In this work, we used CNN-based deep learning models to extract structural information from structural MRI (sMRI) and brain neuron connectivity patterns from … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 3,099 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordLung Cancer Detection Using Regularized Extreme Learning Machine and PCA FeaturesK. Kavitha, Dr. V. Saravana Kumar, V. Bhoopathy et al.When finding abnormalities in target images is time-sensitive, as it is with many cancer tumors, image processing techniques have recently found widespread use across various medical industries to improve images for early detection and treatment stages. In the setting of cancer, where time is of the essence in detecting anomalies within medical imaging, our research takes on further urgency. In … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,302 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordEssential Proteins Discovery Methods based on the Protein-Protein Interaction NetworksLingZhi Zhu, Junling Zhang, Lingya He et al.Essential proteins are closely related to biological survival or reproduction and have important application value in respect of the location of disease genes, disease diagnosis and treatment, drug design. In order to discovery essential proteins, the researchers have proposed experimental approaches, but these methods require laborious and time consuming. With the development of high-throughput sequencing techniques, plenty of computational methods … …American Journal of Biochemistry and Biotechnology, Vol. 13, Issue 4 · 1 Jan 2018 · 8,891 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAnalyzing Effect on Residual Learning by Gradual Narrowing Fully-Connected Layer Width and Implementing Inception Block in Convolution LayerSaurabh SharmaResearch conducted on the advancement of CNN architecture for computer vision problems focuses on strategically choosing and modifying convolution hyperparameters (kernel, pooling, etc.). However, these research works don't exploit the advantage of employing multi fully-connected layers post the core schema to avail further performance improvements, which have been identified as the first research gap. Studies were also conducted to address … …Journal of Computer Science, Vol. 18, Issue 5 · 24 May 2022 · 6,044 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordMedical Image Compression with Lossless Region of Interest Using Adaptive Active ContourR. Loganathan, Y. S. KumaraswamyProblem statement: With increasing bandwidth, digital medical image storage and transmission is a boon to patients and health professionals alike. Medical images are available instantly and avoid the need to carry the data physically. Popular imaging techniques extensively used in medicine include X-Ray, Magnetic Resonance Imaging (MRI), Ultrasound and Computed Tomography (CT). The images produced from the above techniques can … …Journal of Computer Science, Vol. 8, Issue 5 · 1 Mar 2012 · 7,723 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordMammogram Analysis Based on Pixel Intensity Mean FeaturesR. Nithya, B. SanthiProblem statement: In the recent years, Computer Aided Diagnosis (CAD) can be very useful for detection of breast cancer. Mammography can be used as an efficient tool for breast cancer diagnosis. A computer based diagnosis and classification system can reduce unnecessary biopsy. Approach: This study investigates a new approach to the classification of mammogram images based on pixel intensity mean … …Journal of Computer Science, Vol. 8, Issue 3 · 7 Jan 2012 · 7,666 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordChoice Of Input Data Type Of Artificial Neural Network To Detect Faults In Alternative Current SystemsT. Benslimane, B. Chetate, R. BeguenaneThis paper present a study on different input data types of ANN used to detect faults such as over-voltage in AC systems (AC network , induction motor). The input data of ANN are AC voltage and current. In no fault condition, voltage and current are sinusoidal. The input data of the ANN may be the instantaneous values of voltage and … …American Journal of Applied Sciences, Vol. 3, Issue 8 · 31 Aug 2006 · 6,775 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordPERFORMANCE ANALYSIS OF GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURE FEATURES FOR GLAUCOMA DIAGNOSISSakthivel Karthikeyan, N. RengarajanGlaucoma is a multifactorial optic neuropathy disease characterized by elevated Intra Ocular Pressure (IOP). As the visual loss caused by the disease is irreversible, early detection is essential. Fundus images are used as input and it is preprocessed using histogram equalization. First order features from histogram and second order features from Gray Level Co-occurrence Matrix (GLCM) are extracted from the … …American Journal of Applied Sciences, Vol. 11, Issue 2 · 24 Dec 2013 · 7,326 accessesView PDFCite