Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

71 results for “Medical Imaging”
Set a search alert
Research ArticleOpen accessPhrase in the titleImproving Medical Imaging and Blood Flow Measurement by using a New Doppler Effect RelationshipFlorian Ion T. PetrescuThe Doppler Effect represents the frequency variation of the waves, received by an observer which is drawing (coming), respectively it’s removing (going), from a wave spring (source). One proposes to study the Doppler Effect for the light waves, generally for the electromagnetic waves. Doppler effect (or Doppler shift), named after Austrian physicist Christian Doppler who proposed it in 1842 in … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 4 · 14 Oct 2015 · 12,852 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA UDDI Search Engine for SVG Federated Medical Imaging Web ServicesSabah Mohammed, Jinan Fiaidhi, Marshal HahnWith more and more medical web services appearing on the web, web service's discovery mechanism becomes essential. UDDI is an online registry standard to facilitate the discovery of business partners and services. However, most medical imaging applications exist within their own protected domain and were never designed to participate and operate with other applications across the web. However, private UDDI … …Journal of Computer Science, Vol. 2, Issue 4 · 30 Apr 2006 · 7,008 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleThe Impact of XRF-Escape on Energy Resolution of NaI: Tl Scintillation Detectors for Medical Imaging or Gamma-Ray SpectroscopyRaffaele Scafè, Marco Puccini, Rosanna Pellegrini, Roberto PaniThe effect of escape of X-ray fluorescence from scintillator elemental components on the detector energy resolution is investigated from a spectroscopic standpoint, for monolithic and pixelated crystals. Along with these, any other emissions in a given region of interest were also considered. In present spectral evaluations a range of ratios between the areas of the peaks (XRFesc) to (XRFesc + … …American Journal of Applied Sciences, Vol. 21, Issue 1 · 10 Jul 2024 · 5,024 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleReduction of Radiation Effects in Biomedical Imaging Detectors by Technology ChangeEssesse Songa Auguste, Wembe Tafo Evariste, Madinatou Salomon, Belinga Aboudou JeanSilicon is a preferred material in the design of medical imaging detectors. It enables reliable and inexpensive detectors to be produced. However, the operation of this material is compromised when irradiated with high radiation of more than 5 ×1014 particles/cm2of high energy neutrons. The defects caused transform the electrical properties. Therefore, this loss of information compromises the reconstruction of important … …American Journal of Engineering and Applied Sciences, Vol. 14, Issue 3 · 17 Jul 2021 · 6,987 accessesView PDFCite
Research ArticleOpen accessIn the keywordsUMPM-Net: A Multimodal Deep Learning Framework for Colorectal Cancer PrognosisK. Muthuchamy, S K. Piramu PreethikaColorectal cancer (CRC) is one of the most common cancers worldwide, for which early prediction of patient outcomes is important for personalised treatment planning and to improve survival. However, current prediction systems are limited in the fact that they are based on single-modality data and cannot capture the complex interactions between clinical, imaging, and genomic factors. To overcome these shortcomings, … …Journal of Computer Science, Vol. 22, Issue 9 · 20 Sep 2026 · 613 accessesView PDFCite
Research ArticleOpen accessIn the keywordsExplainable MedAttn-ResNet50 for Automated Kidney Tumor Classification from CT Images With Grad-CAM VisualizationD. Vetrithangam, Pramod Kumar, Shilpasree S. et al.Kidney tumor classification from CT imaging remains challenging due to CT-specific intensity variations, tumor heterogeneity, and limited clinically meaningful interpretability in existing deep learning models. To address these limitations, we propose an Explainable MedAttn-ResNet50 framework that integrates radiology-driven preprocessing, multi-scale feature extraction, and medical attention mechanisms within a unified architecture. The preprocessing pipeline applies radiology-inspired intensity normalization, contrast enhancement, and … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,120 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Detailed Preserving Medical Image Denoising Using Cluster-Wise PCA Thresholding and Iterative Mean FilteringMohit Sharma, Ayush Dogra, Anita Gupta et al.Image denoising is a vital process in medical imaging that involves removing noise or distortions introduced during image acquisition. Random noise can degrade image quality and reduce contrast, making accurate analysis more challenging. This paper presents a detail-preserving medical image denoising framework based on a hybrid methodology that combines cluster-wise Principal Component Analysis (PCA) thresholding with Iterative Mean Filtering (IMF). … …Journal of Computer Science, Vol. 22, Issue 4 · 18 Apr 2026 · 1,787 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comprehensive Review of Medical Image Denoising: Techniques, Challenges, Applications and Future DirectionsMohit Sharma, Ayush Dogra, Anita Gupta et al.The concept of noise reduction in medical images plays a vital role in improving image quality and accuracy associated with diagnosis, and facilitating reliable automated analysis. This survey presents a structured overview of medical image denoising, beginning with foundational definitions and noise models for modalities such as MRI and CT. We critically evaluate persistent gaps, including the limited generalizability of … …Journal of Computer Science, Vol. 22, Issue 3 · 28 Mar 2026 · 1,849 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHybrid Deep Learning for Kidney Stone Detection in CT Scans With Noise Reduction and Feature EnhancementU. M. Fernandes Dimlo, Sreenu Banoth, Priti Bihade et al.The identification of kidney stones using CT scans is an essential but difficult effort in medical diagnostics, frequently obstructed by imaging noise and the complexity of manual interpretation. Although conventional methods are widely used, they suffer from inaccuracies and inefficiencies, necessitating the development of automated diagnostic solutions. This study tackles these issues by presenting HDCNRNet, a hybrid deep learning network … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 2,161 accessesView PDFCite
Review ArticleOpen accessIn the keywordsFederated 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