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 accessIn the abstractExplainable 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 abstractA 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 abstractRobust Adversarial Attack Detection via Generative Adversarial Network With Residual Multi-Layer Aggregation Based Contrastive Loss FunctionAmudha Gopalakrishnan, Nalini JosephAdversarial attacks in medical imaging refer to subtle modifications to images that mislead diagnostic systems, resulting in inaccurate diagnoses and assessments. These attacks exploit vulnerabilities in image processing, leading to misclassification or altered visual features that often go unnoticed. This raises serious concerns about the security and reliability of medical diagnosis, directly impacting clinical decision-making and patient safety. This research … …Journal of Computer Science, Vol. 22, Issue 1 · 10 Feb 2026 · 1,742 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 · 2,358 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 · 5,302 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Super-Resolution using Auto-Encoders with Parallel Skip-ConnectionsLisha Pulickal Purushothaman, Jayasree Vadakke KadangoteSuper-resolutionimages are highly desired when employed for numerous analytical purposes andobviously because of their superior attractive visual effect. To create aHigh-Resolution (HR) image from one or more Low-Resolution (LR) images, animage super-resolution technique is used. When dealing with naturalenvironments and settings, it is not always easy to access high-resolutionimages. The main barriers to the same are limitations in acquisition methods.In … …Journal of Computer Science, Vol. 18, Issue 11 · 11 Nov 2022 · 6,081 accessesView PDFCite
Literature ReviewOpen accessIn the abstractA Comprehensive Survey on Tools for Effective Alzheimer’s Disease DetectionN. Vinutha, G. U. Vasanthakumar, P. Deepa Shenoy, K. R. VenugopalNeuroimaging is considered as a valuable technique to study the structure and function of the human brain. Rapid advancement in medical imaging technologies has contributed significantly towards the development of neuroimaging tools. These tools focus on extracting and enhancing the relevant information from brain images, which facilitates neuroimaging experts to make better and quick decision for diagnosing enormous number of … …Neuroscience International, Vol. 9, Issue 1 · 4 Oct 2017 · 10,232 accessesView PDFCite
EditorialOpen accessIn the abstractBig Data and Parkinson’s Disease - from Understanding of Disease to Personalised MedicineYen F. Tai, Nicola PaveseThe advancement of information technology in recent years has generated a huge amount of datasets in all areas of scientific research. This has led to new opportunities to harness the 'Big Data' to improve our understanding of diseases - from investigating disease mechanisms to monitoring treatment responses. The Big Data approach is a data-driven and often hypothesis-free, way of studying … …Neuroscience International, Vol. 7, Issue 1 · 27 Jul 2016 · 7,755 accessesView PDFCite
EditorialOpen accessIn the abstractNanotechnology: Engineering Materials for a Better 21st CenturyMeng Qiao, Xiyun Liu, Lei ZhangToday, we are living in the midst of a technological revolution, where nanotechnology is demonstrating a greater commitment to make people’s everyday lives better. The aim of nanotechnology is to create new materials with desired properties by engineering their nanoscale structures and components. One of the most important impacts of nanotechnology is in medical diagnosis and treatment. Cardiovascular diseases such … …Current Research in Nanotechnology, Vol. 5, Issue 1 · 26 Nov 2014 · 8,737 accessesView PDFCite