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130 results for “Medical Image”
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Research ArticleOpen accessPhrase in the titleComparative Study of the Effect of Lossy and Lossless Block Based Binary Plane Techniques on Medical ImagesNalla Subhash Chandra, Mahaboob Basha Shaik, A. Govardhan, M. BalrajuProblem statement: The general and medical images in specific contain different regions holding information of different significances. To elaborate medical information, the doctor prefers to focus on certain selected region (s) of interest. So for medical images the diagnostically important regions must be preserved at high quality, whereas the rest of the image is required only in a contextual sense. … …Journal of Computer Science, Vol. 6, Issue 11 · 23 Oct 2010 · 7,381 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Cloud-Based Approach for Privacy-Preserving Medical Image Retrieval: Leveraging Local Features and PCA in Two Efficient StepsM Geetha Yadav, SP ChokkalingamThe major challenges of content-based image retrieval are searching, ranking, and retrieving in secure mode. In this article, we propose a two-step security approach for each database image, utilizing encryption mechanisms and cloud technology. In this approach, the watermark-embedded encrypted images, along with the efficient feature vector database and the list of authenticated users, will be stored in the cloud. … …Journal of Computer Science, Vol. 20, Issue 12 · 4 Nov 2024 · 4,300 accessesView PDFCite
Review ArticleOpen accessPhrase in the titleFederated Learning for Analysis of Medical Images: A SurveyMuhammad Imran Sharif, Mehwish Mehmood, Md Palash Uddin et al.Machine learning models trained in medical imaging can help in the early detection, diagnosis, and prognosis of the disease. However, it confronts two major obstacles: deep learning models require access to a substantial amount of imaging data, which is a hard constraint, and the patient data is private and sensitive, so it cannot be shared like 1 other imaging data … …Journal of Computer Science, Vol. 20, Issue 12 · 28 Oct 2024 · 11,838 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleMEDICAL IMAGE SEGMENTATION FOR ANATOMICAL KNOWLEDGE EXTRACTIONMs Maya Eapen, Reeba KorahComputed Tomography-Angiography (CTA) images of the abdomen, followed by precise segmentation and subsequent computation of shape based features of liver play an important role in hepatic surgery, patient/donor diagnosis during liver transplantation and at various treatment stages. Nevertheless, the issues like intensity similarity and Partial Volume Effect (PVE) between the neighboring organs; left the task of liver segmentation critical. The … …Journal of Computer Science, Vol. 10, Issue 7 · 22 Feb 2014 · 6,465 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Review on Recent Research and Implementation Methodologies on Medical Image SegmentationS. K. Somasundaram, P. AlliProblem statement: Image segmentation plays a very important role in digital imaging applications for classifying the anatomical structures and other Regions of Interest. Segmentation refers to the process of identifying and isolating the surface and regions of the digital image which corresponds to the structural units. Approach: In the past few decades, many methods have been proposed to segment the … …Journal of Computer Science, Vol. 8, Issue 1 · 4 Nov 2011 · 7,121 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAutomatic Skin Lesion Diagnosis and Medical ReportGeneration Based on Image CaptioningAbdelouahed Sabri, Chaimae Zouitni, Hamza El Medhoune, Abdellah AarabCaptioning or textual description of the visual content of imagesinvolves generating meaningful words and sentences to describe the contentof an image. This work lies at the crossroads of Natural LanguageProcessing (NLP) and computer vision. When dealing with medical imagesand especially skin lesions, it goes beyond simple classification to generatedetailed textual reports describing the skin lesion's conditioncomprehensively. Such reports are crucial … …Journal of Computer Science, Vol. 21, Issue 5 · 13 May 2025 · 5,432 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Enhanced Approach for Medical Brain Image EnhancementJ. Umamaheswari, G. RadhamaniProblem statement: One of the most common degradations in medical images is their poor contrast quality and noise. The DICOM image consists of speckle (multiplicative noise). While the image is enhanced, the multiplicative noise present in the image is also enhanced. Approach: This study describes the hybrid method to improve the image quality of Digital Imaging and Communications in Medicine … …Journal of Computer Science, Vol. 8, Issue 8 · 27 Jul 2012 · 6,969 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Integrated Disease Progression Model to Analyze Electronic Health Records With Multimodal Datasets Using Deep Learning TechniquesThulaganyo Dimakatso, Venumadhav Kuthadi, Rajalakshmi Selvaraj, Othapile DinakenyaneIn contemporary clinical environments, precisely simulating the emergence of disease is an intricate task owing to heterogeneously derived data and variability in the record of diagnoses. The research presents a stable classification model that integrates image data with formalized patient data to track patterns in disease through various stages. The suggested approach combines a multi-stage analytical methodology that includes systematic … …Journal of Computer Science, Vol. 22, Issue 2 · 19 Feb 2026 · 1,686 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRobust Adversarial Attack Detection via Generative Adversarial Network With Residual Multi-Layer Aggregation Based Contrastive Loss FunctionAmudha Gopalakrishnan, Nalini JosephAdversarial attacks in medical imaging refer to subtle modifications to images that mislead diagnostic systems, resulting in inaccurate diagnoses and assessments. These attacks exploit vulnerabilities in image processing, leading to misclassification or altered visual features that often go unnoticed. This raises serious concerns about the security and reliability of medical diagnosis, directly impacting clinical decision-making and patient safety. This research … …Journal of Computer Science, Vol. 22, Issue 1 · 10 Feb 2026 · 1,749 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOptiCNN: Local thresholding segmentation and CNN with SVM Approach for Diabetic Retinopathy Detection and Classification of Fundus ImagesAnju Mishra, Mrinal Pandey, Laxman SinghDiabetic Retinopathy (DR) is a progressive eye disease that can lead to vision loss and blindness if left untreated. Ophthalmologists diagnose DR using medical imaging modalities such as fundus photography and optical coherence tomography (OCT); however, manual interpretation of these images is time-consuming and subject to inter-observer variability. While DR is irreversible, vision loss can be prevented through early detection … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,162 accessesView PDFCite