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130 results for “Medical Image”
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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 · 7,482 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 · 7,855 accessesView PDFCite
Research ArticleOpen accessIn the abstractEffectual Deep Learning Based Digital Image Forgery Detection Model Using Ameliorate CNN, VGG 16 and VGG 19 for Copy Move and Image Splicing Classification With Enhanced PerformancePreeti Dhiman, Usha ChauhanIn this research, a pioneer passive approach for detecting and localizing tampering in images is proposed. In the past, image forgeries have created a huge impact in the world. Developments of various image processing technologies made it easier to tamper images with the objective to cover up or hide a significant feature in an image. In some situation, such as … …Journal of Computer Science, Vol. 22, Issue 10 · 3 Oct 2026 · 580 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 · 536 accessesView PDFCite
Research ArticleOpen accessIn the abstractMedFusion: A Unified Multimodal Framework for Visual Question Answering and Explainable Medical RecommendationSatyajit Mahapatra, Jibitesh Mishra, Kumar Janardan Patra et al.In clinical decision-making, the ability to ask visual questions about medical images and receive accurate, personalized, and interpretable recommendations can significantly enhance practitioner support systems. This paper presents MedFusion, a unified multimodal framework that integrates Visual Question Answering (VQA), personalized medical recommendation, and explainability within a single architecture. The proposed model employs co-attention–based visual–textual fusion augmented with retrieval-enhanced reasoning to … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,370 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 · 1,470 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Approach for Differentiating AI-Generated and Real Images Using Gabor and Color Layout Filters (GF and CLF)G. Ayyappan, A. Thankaraj, S. Surendran et al.The emergence of generative AI images has profoundly upended the art world. Distinguishing AI-generated images from human-created artwork is increasingly challenging. If this issue remains unresolved, dishonest individuals may exploit those who are willing to pay more for original artwork and businesses whose stated policies exclude AI graphics. There are a number of methods for differentiating AI photos from human … …Journal of Computer Science, Vol. 22, Issue 2 · 3 Mar 2026 · 1,756 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Image Clarity Using Adaptive RegularizationKavya T M, Yogish Naik G RIn many domains such as digital photography, remote sensing, and medical imaging, improving image clarity is essential. It is frequently difficult for traditional methods to strike a balance between preserving significant image details and reducing noise. This work presents a novel method for improving images by utilizing adaptive regularization techniques. In order to effectively reduce noise and preserve fine details, … …Journal of Computer Science, Vol. 21, Issue 9 · 15 Oct 2025 · 2,368 accessesView PDFCite
Research ArticleOpen accessIn the abstractLung Cancer Detection Using Regularized Extreme Learning Machine and PCA FeaturesK. Kavitha, Dr. V. Saravana Kumar, V. Bhoopathy et al.When finding abnormalities in target images is time-sensitive, as it is with many cancer tumors, image processing techniques have recently found widespread use across various medical industries to improve images for early detection and treatment stages. In the setting of cancer, where time is of the essence in detecting anomalies within medical imaging, our research takes on further urgency. In … …Journal of Computer Science, Vol. 20, Issue 10 · 5 Aug 2024 · 5,311 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 · 6,786 accessesView PDFCite