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71 results for “medical imaging”
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Research ArticleOpen accessIn the keywordsA Robust Medical Image Fusion Based on Synthetic Focusing Degree Criterion and Special Kernel Set for Clinical DiagnosisDawa Chyophel Lepcha, Bhawna Goyal, Ayush Dogra et al.Medical imaging has been widely used to diagnose diseases over the last two decades. Medical professionals still struggle to diagnose diseases using a single modality since there is a shortage of data in this domain. Therefore, images of specific organs with diseases from a variety of medical imaging systems can be combined using a technique called image fusion. Medical image … …Journal of Computer Science, Vol. 20, Issue 4 · 6 Feb 2024 · 5,625 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCardiovascular Disease Prediction through Ensembled Transfer Learning on Cardiac Magnetic Resonance ImagingSibu Cyriac, Sivakumar R., Nidhin RajuCardiovascular Diseases (CVD) cause more deaths worldwide than most of the other diseases. The diagnosis of cardiovascular disease from Magnetic Resonance Imaging plays a major role in the medical field. The technological revolution contributed a lot to increase the effectiveness of CVD diagnosis. Many Artificial Intelligence methods using Deep Learning models are available to assist the cardiologist in the diagnosis … …Journal of Computer Science, Vol. 18, Issue 11 · 2 Nov 2022 · 6,169 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDenoising Methods for MRI ImagerySamuel KozaitisThere are several new denoising algorithms that may be useful for magnetic resonance imaging. We compared the performance of some of the latest denoising algorithms with those that have been developed specifically for MRI imagery. We found that the latest approaches show impressive performance in terms of mean squared error, but a measure based on perceptual quality may be needed … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 3 · 30 Aug 2017 · 7,478 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCOMPUTER AIDED SEGMENTATION OF BRAIN TISSUES USING SOFT COMPUTING TECHNIQUESD. Ramkumar, I. Jacob Raglend, K. BatriIn this study, an efficient computer aided classification of brain tissue in to Gray Matter (GM), White Matter (WM) and Cerebro-Spinal Fluid (CSF) is proposed. The proposed work consists of the following sub blocks like denosing, feature extraction and Classifier. This initial partition is performed by ANFIS after extracting the textural features like local binary pattern and histogram features. The … …American Journal of Applied Sciences, Vol. 11, Issue 6 · 17 Apr 2014 · 6,662 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSelf Organizing Map Cluster Approach for Wavelet Based Medical Image CompressionS. Sridevi, V. R. Vijayakumar, V. Sutha JebaKumariDigital medical powerful tools for diagnosis, treatment and surgery and plays a vital role in modern healthcare delivery. Large storage capacity is needed for storing these images and for transmitting them. This leads to the strong demand for digital medical image compression and reliable transmission. In this study, we have applied three compression methods to medical images. In all the … …American Journal of Engineering and Applied Sciences, Vol. 5, Issue 4 · 2 Jan 2013 · 7,422 accessesView PDFCite
Research ArticleOpen accessIn the keywordsWarped Optical-Flow Inter-Frame Reconstruction for Ultrasound Image EnhancementBalza Achmad, Mohd Marzuki Mustafa, Aini HussainProblem statement: Optical flow inter-frame enhancement is one of the techniques to improve the quality of ultrasound images by reducing the speckle noise. The performance depends on accuracy of the optical flow inter-frame reconstruction which is a part of the technique. The speckle noise of an ultrasound image forms certain pattern, of which size of the speckle varies depends on … …Journal of Computer Science, Vol. 7, Issue 10 · 6 Aug 2011 · 7,212 accessesView PDFCite
Research ArticleOpen accessIn the keywordsComparison of Denoising Algorithms for Urban ScenesSamuel KozaitisSeveral new denoising algorithms have recently been presented that display comparable performance and it is unclear which provide the best results. We used the practical example of urban scenes to compare two of the top-performing algorithms. We found that when using the practical case of quantizing input and output imagery, the results were different than when using the conventional method … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 2 · 20 Jun 2017 · 7,849 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Adaptive Region Growing Algorithm with Support Vector Machine Classifier for Tuberculosis Cavity IdentificationK. Meenakshi Sundaram, C. S. RavichandranThe major world health menace is Tuberculosis (TB) that has the effect on one-third of the global population and millions of new infections are occurring every year. The cavities in the upper lung zone are a strong indicator that the disease has developed into a highly contagious state. The study includes 52 Chest X-ray images with Tuberculosis and 43 Chest … …American Journal of Applied Sciences, Vol. 10, Issue 12 · 29 Oct 2013 · 7,067 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Adaptive Detail Preserving Modified Progressive Pca Thresholding Based Image DenoisingN. Anilkumar, S. Radhakrishnan, Shaik Syed Basha et al.Radiologists use medical imaging tools to assess the anatomy and function of interior organs. However, medical images are frequently distorted by various types of noise generated during the capture, transmission, and reconstruction operations, which can dramatically reduce image quality and hide critical diagnostic features. As a result, developing effective denoising algorithms that suppress noise while maintaining structural information remains a … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 529 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing 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