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98 results for “medical images”
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Research ArticleOpen accessPhrase in the titleImproving Diagnostic Viewing of Medical Images using Enhancement AlgorithmsHanan Saleh S. Ahmed, Md Jan NordinProblem statement: Various images are low quality and difficultly to detect and extract information. Therefore, the image has to get under a process called image enhancement which contains an aggregation of techniques that look for improving the visual aspect of an image. Medical images are one of the fundamental images, because they are used in more sensitive field which is … …Journal of Computer Science, Vol. 7, Issue 12 · 18 Oct 2011 · 7,991 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleClinical Assessment of Watermarked Medical ImagesJasni Mohamad Zain, Abdul Rani M. Fauzi, Azian A. AzizProblem statement: Digital watermarking provides security to medical images. Watermarking in Region Of Interest (ROI) however distorts medical images but it is known that the resulting loss of fidelity is visually imperceptible. Approach: Clinical assessment will objectively evaluate the distortion on medical images to see whether or not medical diagnosis is altered. We used 75 medical images consisting of x-rays, … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 8,125 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Hybrid Fuzzy Neural Networks for the Detection of Tumors in Medical ImagesN. Benamrane, A. Freville, R. NekkacheIn this study, we propose an approach to detect suspect zones or tumors in medical images. The idea is to define with precision the existence of different kinds of lesions using a hybrid system, which combines Fuzzy Neural Networks and Expert System. After applying a method of image segmentation to extract regions (by region growing algorithm or by mathematical morphology … …American Journal of Applied Sciences, Vol. 2, Issue 4 · 30 Apr 2005 · 6,873 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleNon-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 accessPhrase in the titleA 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 accessPhrase in the titleMedical Images Registration based on Normalized Dissimilarity IndexAmina KHARBACH, Mouad EL OMARI, Amar MARDANI et al.Image registration is an essential step in a large number of processing chains for medical images. It is used to align two images taken at different times and from different sensors as well. In this paper, we are interested in the rigid registration and similarity measures. We describe a new registration approach, based on the normalized dissimilarity index that results … …Journal of Computer Science, Vol. 13, Issue 9 · 28 Sep 2017 · 7,527 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleIndexing Medical Images Using the Wavelet Transform: Application to Retinal ImagesSouad Meziane Tani, Abdelhafid BessaidContent-Based Image Retrieval Systems (CBIR) provide effective support to the doctor to find relevant images using their visual content. Current medical systems are unable to provide accurate and precise results. To solve this problem, effective indexing algorithms are required to extract the contents of the images. In this study, the method of indexing image from the energy coefficients of the … …Current Research in Bioinformatics, Vol. 2, Issue 2 · 1 Jul 2014 · 6,691 accessesView PDFCite
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 · 7,380 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAn Efficient Low Complexity Lossless Coding Algorithm for Medical ImagesS. E. Ghrare, M.A. Mohd. Ali, K. Jumari, M. IsmailProblem statement: Nowadays a large number of various medical images are generated from hospitals and medical centers with sophisticated image acquisition devices, the movement toward digital images in radiology presents the problem of how to conveniently and economically store, retrieve and transmit the volume of digital images. Thus digital image data compression is necessary in order to solve this problem. … …American Journal of Applied Sciences, Vol. 6, Issue 8 · 31 Aug 2009 · 7,091 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 · 11,824 accessesView PDFCite