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106 articles for “medical image processing”
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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Application of Machine Learning Techniques for Tongue Diagnosis in Ayurveda
Abstract: The analysis of tongue image is a very crucial approach in order to evaluate human health in Ayurveda medication. As a result of the modification in tongue color might counsel physical or mental disorders. Many tongue color quantification strategies for tongue diagnosis are published by many researchers in Chinese medication. However, reliable tongue color analysis algorithms are limited for Ayurveda medicine. The main objective of this paper is to apply …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 1, 2020 · pp. 8–14 Read article
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MediSense AI - Smart Health Analysis System
Abstract: MediSense AI is a revolutionary health analysis system that empowers users by transforming complex medical data into understandable insights. This platform utilizes advanced technologies, particularly natural language processing and machine learning, to make intricate medical terminologies accessible to individuals without a healthcare background. Leveraging Llama 3, a cutting-edge AI model developed by Meta AI, the system can analyze various forms of medical data, including the ability for users to upload …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 20–30 Read article
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Nonlinear Fusion Techniques Comparative Analysis For The Confiscation of Reconnaissance Effects from the Fused Image
Abstract: Image fusion is the process of combining relevant information from two or more images into a single image. It provides a useful tool to integrate multiple images into a composite image. The resulting image will be more informative than any of the input images. Recently the new problem found with the fused image is about reconnaissance effects are present which are inexorable while smearing to the medical field. For solving …
Published in Recent Trends in Electronics Communication Systems · Vol. 2, Issue 2, 2015 · pp. 37–40 Read article
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Machine Learning in Nuclear Medical Applications: A Review of Research Frontiers
Abstract: Nuclear medicine, encompassing PET, SPECT, and targeted radionuclide therapy, generates high-dimensional, quantitative data uniquely suited for machine learning (ML) analysis. This review synthesizes current research applications of ML across six key domains. Positron emission tomography (PET), single-photon emission computed tomography (SPECT), and targeted radionuclide therapy are examples of nuclear medicine modalities that generate high- dimensional, quantitative datasets that are particularly well-suited for machine learning (ML)-driven analysis. These imaging methods provide …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 19–24 Read article
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Cardiovascular Image Segmentation in Computed Tomography Angiography ImagesUsing Deep Learning Approaches
Abstract: In present time, the cardiovascular disease is one of the common causes of mortality in human. In field of medical science, Heart angiography is one of the processes to testing of heart disease. Heart angiography identifies the abnormality in heart vessels. There are mainly two approaches to identify the heart disease. Former approach is the invasive and latter one is the non-invasive approaches. Invasive process is a painful diagnostic procedure …
Published in Recent Trends in Electronics Communication Systems · Vol. 10, Issue 1, 2023 · pp. 20–27 Read article
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Heart Disease Evaluation Through Echocardiography Using CNN, ResetNet50, VGG16, and Image Processing
Abstract: Heart conditions stand out as primary contributors to untimely mortality among adults aged 30 and above, notably among those grappling with elevated cholesterol levels and diabetes. Detecting such ailments often necessitates the use of an echocardiogram, providing an intricate portrayal of the heart. However, precise analysis hinges on both the proper functioning of the echocardiogram apparatus and the proficiency of a skilled radiologist, a condition not always met. Manual scrutiny …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 25–35 Read article
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Effective CBIR System Using Color Histogram and Distance Measures
Abstract: AbstractInterests to precisely retrieve desired images from databases of medical images are developing every day. Certain features define the images; on the basis of those, the retrieval of images is facilitated. These components incorporate texture, color, shape and region. A lot of work has been done in this direction to discover the new ways to use these features in image retrieval process. In this study, we exhibit an overview of …
Published in Journal of Web Engineering & Technology · Vol. 6, Issue 1, 2019 · pp. 11–14 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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Analysis of Image Watermarking Techniques against Various Noise Attacks for Medical Images using Genetic Algorithm (GA)
Abstract: In this paper, we have presented a dual secure digital image watermarking algorithm based on discrete wavelet transforms (DWT), lifting wavelet transforms (LWT) and singular value decomposition (SVD) using genetic algorithm (GA) for medical images. The natural image is chosen as cover image and is decomposed up to three levels using discrete wavelet transform. The medical image is chosen as a watermark. The genetic algorithm is used to embed and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 2, Issue 3, 2015 · pp. 36–44 Read article
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Magnetic and Radioactive Nanoparticles for Improved Theranostics and AI Assisted Radiation Therapy
Abstract: Nanoparticles based therapeutic and theranostics technique is becoming an active area of research in nanomedicine. The sensitivity, biocompatibility, and stability of magnetic and radioactive nanoparticles determine their functionality. This research highlights the impacts of magnetic and radioactive nanoparticles on therapeutic techniques namely, cell therapy, gene therapy, and tissue regeneration. Then, it is intended to brief a principal role of these therapeutic techniques to envisage theranostics medicine and radiation therapy using …
Published in International Journal of Advance in Molecular Engineering · Vol. 3, Issue 2, 2025 · pp. 10–21 Read article
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Transforming Healthcare Through Big Data: Applications, Challenges, and Future Perspectives
Abstract: Healthcare institutions produce substantial amounts of information through electronic health records, laboratory systems, medical imaging technologies, patient monitoring devices, and various digital healthcare platforms. Managing and interpreting these continuously growing datasets through conventional approaches can be difficult and time-consuming. Big Data technologies offer advanced methods for storing, processing, and analyzing healthcare information efficiently, enabling healthcare professionals to obtain valuable insights for clinical and administrative purposes. This review explores the growing …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 2, 2026 · pp. 1–9 Read article
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Genetic Algorithms Molecular Effect Model Optimization for High-temperature Superconductors Tin and Thallium Classes
Abstract: Genetic algorithms software was applied in 3D Graphical and Interior Optimization methods for two high-temperature Superconductors (HTSCs) classes. Namely, Tin (Sn) class with (TC>0°), and Thallium (Tl) one subject to (TC˂0°, TC>0°) in Molecular Effect Model (MEM). Results include mathematical Tikhonov Regularization Functionals algorithms for this group of HTSCs without using logarithmic changes. Results also show the contrasts between these two classes for Molecular Effect Model (MEM) hypothesis. Solutions show …
Published in Recent Trends in Programming languages · Vol. 9, Issue 3, 2022 · pp. 1–16 Read article
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Systematic Review on: Peptic Ulcer and Its Management
Abstract: Peptic ulcer disease (PUD), which affects 5–10% of people worldwide, is still a significant global health concern. Gastric acid and pepsin's corrosive effects cause mucosal injury in the stomach, duodenum, or lower oesophagus. Long-term use of nonsteroidal anti-inflammatory drugs (NSAIDs) and Helicobacter pylori infection are the primary reasons. This review's goal is to examine PUD's aetiology, risk factors, pathophysiology, clinical symptoms, diagnostic methods, and evidence-based treatment modalities. PubMed, Google Scholar, …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 Read article
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Systematic Review on: Peptic Ulcer and Its Management
Abstract: Peptic ulcer disease (PUD), which affects 5–10% of people worldwide, is still a significant global health concern. Gastric acid and pepsin's corrosive effects cause mucosal injury in the stomach, duodenum, or lower oesophagus. Long-term use of nonsteroidal anti-inflammatory drugs (NSAIDs) and Helicobacter pylori infection are the primary reasons. This review's goal is to examine PUD's aetiology, risk factors, pathophysiology, clinical symptoms, diagnostic methods, and evidence-based treatment modalities. PubMed, Google Scholar, …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 · pp. 60–64 Read article
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Medical Science in the Digital Era: A Comprehensive Study on Computing in Healthcare
Abstract: Adding computers to medical science has changed how healthcare is delivered, how research is done, and how well patients do. This article talks about the many ways that computer technology is used in modern medicine, such as for diagnostic imaging, electronic health records (EHRs), telemedicine, surgical robotics, and research that is based on data. Improvements in artificial intelligence (AI) and machine learning have made it possible to make more accurate …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 Read article
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A Novel Deep CNN Model for COVID-19 Detection based on Lung CT Images
Abstract: In recent months, worldwide society has been destroyed by COVID-19 (Coronavirus Disease 2019), a catastrophic contagious illness that has ravaged the whole world. Deep learning (DL) approaches are the most widely used strategies for chest CT scan processing and illness prediction in the medical field. COVID-19 is infectious sickness that mostly influences the lungs also has the potential to be fatal if left untreated in its extreme form. It also …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 1, 2022 · pp. 1–14 Read article
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DeMe-Net Model to Diagnose Skin Cancer Disease from Skin Lesion
Abstract: Skin cancer is a quite common disease in the world and Melanoma is one of the serious types of skin cancer. It begins in melanocyte cells. Skin irritation or tanning due to UV radiation triggers changes in melanocytes, leading to uncontrolled growth of cells. It can potentially develop and spread if it is not treated early. The biopsy is a traditionally used method to diagnose skin cancer in which a …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 3, 2021 · pp. 10–20 Read article
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Energy-efficient Image Classification on Edge Devices: Implementation and Evaluation
Abstract: Image classification is a computer vision problem where an algorithm determines a class or label for a given image. Various real-time applications like object recognition, medical diagnosis, person recognition, etc. Image classification property on edge devices is useful for autonomous vehicles, surveillance, and healthcare and internet of things deployments. The advancement of deep learning based methods and graphics processing units (GPU) devices allows efficient processing locally. The study utilizes a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 10–18 Read article