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117 results for “Images Segmentation”
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Research ArticleOpen accessIn the keywordsImplementation of Computer Aided Diagnosis System Based on Parallel Approach of Ant Based Medical Image SegmentationJayabalan Jaya, Keppanagowder ThanushkodiProblem statement: The aim of this study is to develop Computer Aided Diagnosis (CAD) system for the detection of brain tumor by using parallel implementation of ACO system for medical image segmentation applications due to the rapid execution for obtaining and extracting the Region of Interest (ROI) from the images for diagnostic purposes in medical field. Approach: For ROI segmentation, … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 8,130 accessesView PDFCite
Research ArticleOpen accessIn the keywordsComputer Aided Diagnosis System for Stone Detection and Early Detection of Kidney StonesMs. P.R. Tamilselvi, Dr. P. ThangarajProblem statement: Most of the previous study in diagnosis of kidney stone identifies a mere presence or absence of the stones in the kidney. However proposal in our study even present an early detection of kidney stones which helps to change the diet conditions and prevent the formation of stones. Approach: The study presented a scheme for ultrasound kidney image … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 8,848 accessesView PDFCite
Review ArticleOpen accessIn the keywordsChallenges of Breast Cancer Detection Based on Histopathology ImagesAlaa Mohamed Youssef, Aliaa Abdel-Haleim Abdel-Razik Youssif, Wessam El BehaidyArtificial Intelligence (AI) is rapidly evolving every day to become increasingly potent and dependable. AI systems are becoming more sophisticated and are being utilized across various domains with the goal of enhancing human existence. Within the healthcare system, artificial intelligence finds application in handling and documenting large volumes of medical data, conducting analyses of healthcare systems, advancing pharmaceutical development, and … …Journal of Computer Science, Vol. 20, Issue 7 · 17 Apr 2024 · 4,942 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Pre-Processing Techniques to Improve DBT Classification Accuracy With CNN ResNet-50Qodri Aziz, Slamet Riyadi et al.Digital Breast Tomosynthesis (DBT) is a three-dimensional imaging technology that is meant to determine breast cancer more accurately than regular mammograms. But low contrast and noise can make DBT images less clear, which can make deep learning-based classification less accurate. This study seeks to assess the impact of diverse preprocessing techniques on breast cancer classification outcomes utilizing the ResNet-50 Convolutional … …Journal of Computer Science, Vol. 22, Issue 10 · 21 Oct 2026 · 349 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion PredictionSugandha Chakraverti, Tejaswi Khanna, Vijay ShuklaLiver lesions are abnormal growths that can develop for various reasons, some of which are noncancerous (benign) while others are cancerous. Machine learning and, deep learning techniques are employed for liver health assessment and lesion detection, but the quality and, diversity of training data can hinder the performance, leading to overfitting or underfitting. These models often need extensive pre-processing and … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 372 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancing Digital Forgery Detection: A Comparative Analysis of U-Net, Buster Net, Efficient B0+ U-Net, and VGG 16+ U-Net ModelsPreeti Dhiman, Usha ChauhanForgery Detection in the area of digital images is indispensable for insuring authenticity, particularly in detecting Copy-Move, Splicing. In this research, a meticulous analysis of latest learning architectures i.e. U-Net, Buster Net, Efficient B0+U-Net and VGG16+U-Net are compared for the detecting these types of forgeries. U-Net is popular due to its potent segmentation capabilities to provide pixel-level forgery localization while … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 383 accessesView PDFCite
Research ArticleOpen accessIn the abstractBrain Tumor Segmentation and Classification Using HardNet Transformer With Gated Recurrent Unit ModelSaida D, Srinivas Adepu, Thade Lakshmi Devi et al.The uncontrolled growth of brain tumor cells presents a severe health risk, making early diagnosis and accurate classification essential for improving treatment outcomes. However, the existing approaches used for segmentation fail to delineate the tumor regions accurately due to a lack of global contextual information of brain tumors, resulting in poor classification performance. To overcome this limitation, this research proposes … …Journal of Computer Science, Vol. 22, Issue 9 · 26 Sep 2026 · 630 accessesView PDFCite
Research ArticleOpen accessIn the abstractMorphological Database and Quantification of Liberica Coffee Beans Using a Hybrid CNN ModelDioneces O. Alimoren, Francis G. Balazon, Jonnah R. Melo et al.Traditional evaluation of Liberica coffee (Kapeng Barako) in Batangas is commonly performed through manual visual inspection and sensory judgment, which are slow, subjective, and difficult to reproduce across farms, buyers, and grading personnel. These limitations can lead to inconsistent quality classification, weak traceability, and reduced bargaining power for local producers. This study develops and validates a web-based morphological analysis system … …Journal of Computer Science, Vol. 22, Issue 8 · 24 Aug 2026 · 1,337 accessesView PDFCite
Research ArticleOpen accessIn the abstractPolar Disentangled Non-Local Convolutional Neural Network for Skin Cancer Classification Using Dermoscopy ImagesUsha Thirugnanam, Nalini JosephSkin cancer classification is the process of identifying and categorizing various types of skin lesions into cancerous and non-cancerous. This process is performed to achieve accurate detection, which minimizes the risk of severe health complications. However, classifying the severity of skin lesion images is a difficult task because of subtle and overlapping visual patterns, which could lead to inaccurate performance. … …Journal of Computer Science, Vol. 22, Issue 6 · 16 Jun 2026 · 1,207 accessesView PDFCite
Research ArticleOpen accessIn the abstractLess Biased Approach for Sandstone Pore SegmentationDaffa Abiyyu Murtadha Kurnia, Iman Herwidiana KartowisastroReservoir characterization is a fundamental process in estimating reserves within petroleum and hydrogeological systems, where the precise determination of pore space dictates the validity of fluid flow models. Although X-Ray Computerized Tomography (XRCT) has become the standard non-destructive evaluation method for visualizing the internal structure of rocks, the data interpretation process still faces challenges during the image segmentation stage. Conventional … …Journal of Computer Science, Vol. 22, Issue 6 · 15 Jun 2026 · 1,191 accessesView PDFCite