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30 results for “Medical Image Classification”
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Research ArticleOpen accessIn the abstractRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,644 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Approaches for Early Detection of Skin Cancer Disease Detection Using Segmentation and Classification with Severity AnalysisPunam R. Patil, Ritu TandonThe utmost prevalent type of the disease, skin cancer claims millions of lives every year, poses a serious public health threat particularly melanoma, which is often fatal if not detected early. Early diagnosis is crucial, yet traditional methods frequently fall short due to image quality limitations and the complexity of visual differentiation. With an emphasis on severity analysis, this study … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 2,051 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomatic 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 · 5,422 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Guided Anatomical Landmark and Abnormality Detection for Autonomous Endoscopy ExaminationMd Shakhawat Hossain, Munim Ahmed et al.Aabakken, L., Barkun, A. N., Cotton, P. B., Fedorov, E., Fujino, M. A., Ivanova, E., Kudo, S., Kuznetzov, K., De Lange, T., Matsuda, K., Moine, O., Rembacken, B., Rey, J., Romagnuolo, J., Rösch, T., Sawhney, M., Yao, K., & Waye, J. D. (2014). Standardized endoscopic reporting. Journal of Gastroenterology and Hepatology, 29(2), 234–240. https://doi.org/10.1111/jgh.12489 Aliyi, S., Dese, K., & Raj, … …Journal of Computer Science, Vol. 20, Issue 8 · 29 May 2024 · 6,783 accessesView PDFCite
Research ArticleOpen accessIn the abstractNon-Decimated Wavelet Transform and Vector Quantization for Lossy Medical Images CompressionHend A. Elsayed, Qusay E. Majeed, Mohammed M. El SherbinyThis study presents a new approach for lossy medical image compression using vector quantization. Recently, the digital image has been a reliable replacement for a hard copy of medical images, therefore, an effort has been made to ensure maintaining high-quality images to use for archiving, classification, or automated diagnostics support. Although the medical application contains all sorts of the images … …Journal of Computer Science, Vol. 19, Issue 3 · 24 Feb 2023 · 5,403 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Convolutional Neural Wavelet Network for Classification of Medical ImagesRamzi Ben Ali, Ridha Ejbali, Mourad ZaiedThis work present a new solution for medical image classification using the Neural Network (NN) and Wavelet Network (WN) based on the Fast Wavelet Transform (FWT) and the Adaboost algorithm. This method is divided in two stages: The learning stage and the classification stage. The first consists to extract the features using the FWT based on the MultiResolution Analysis (MRA). … …Journal of Computer Science, Vol. 14, Issue 11 · 11 Nov 2018 · 7,620 accessesView PDFCite
Research ArticleOpen accessIn the abstractContent Based Medical Image Retrieval using Binary Association RulesAkila, Uma MaheswariIn this study, we propose a content-based medical image retrieval framework based on binary association rules to augment the results of medical image diagnosis, for supporting clinical decision making. Specifically, this work is employed on scanned Magnetic Resonance brain Images (MRI) and the proposed Content Based Image Retrieval (CBIR) process is for enhancing relevancy rate of retrieved images. The pertinent … …Journal of Computer Science, Vol. 9, Issue 6 · 30 May 2013 · 6,548 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Fuzzy Neural Approach for Medical Image RetrievalC. Sriramakrishnan, A. ShanmugamImage retrieval based on a query image is necessary for effective and efficient use the information that is stored in medical image databases. Medical Image Retrieval is difficult as not only the localization and directionality of human visual system is to be considered but also the pathological condition. Image identification and segmentation for feature extraction pose a challenge to image … …Journal of Computer Science, Vol. 8, Issue 11 · 8 Sep 2012 · 6,666 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Optimal Approach for Medical Image AnalysisJ. Umamaheswari, G. RadhamaniProblem statement: Image segmentation is the process that subdivides an image into its constituent parts and extracts the objects. It is one of the most critical tasks in automatic image analysis because the subdivided results will affect all the subsequent processes of image analysis, such as object representation and description, feature measurement and even the following higher level tasks such … …Current Research in Bioinformatics, Vol. 1, Issue 1 · 6 Jun 2012 · 9,513 accessesView PDFCite
Research ArticleOpen accessIn the abstractContent Based Medical Image Retrieval with Texture Content Using Gray Level Co-occurrence Matrix and K-Means Clustering AlgorithmsB. Ramamurthy, K. R. ChandranProblem statement: Recently, there has been a huge progress in collection of varied image databases in the form of digital. Most of the users found it difficult to search and retrieve required images in large collections. In order to provide an effective and efficient search engine tool, the system has been implemented. In image retrieval system, there is no methodologies … …Journal of Computer Science, Vol. 8, Issue 7 · 24 May 2012 · 7,448 accessesView PDFCite