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106 articles for “medical image processing”
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Comparison Performance Analysis of Multi-Wavelet Based Watermarking Techniques for Medical Images Using Genetic Algorithm (GA)
Abstract: In this paper, the scaling factor of the watermark is the significant parameter that helps in improving the imperceptibility and robustness against attacks. The tradeoff between the imperceptibility and robustness is considered as an optimization problem and is solved by applying genetic algorithm (GA). The water marking is proposed to be implemented using a hybrid approach which encompasses discrete wavelet transforms (DWT), lifting wavelet transforms (LWT) and singular value decomposition …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 1, 2016 · pp. 15–23 Read article
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Vein Detector using Image Processing
Abstract: Abstract: Most of the doctors face problem while giving dose of medicine using syringe to patients who have darker skin tone, have wrinkled skin, small children’s and people who have scorch marks or burned skin. Due to such problems, doctors may insert the syringe in wrong place or it may become harder for doctors to find veins of such patients. This Paper presents a new methodology of Vein Finder Which …
Published in Recent Trends in Electronics Communication Systems · Vol. 6, Issue 1, 2019 · pp. 31–34 Read article
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A Review on Brain Tumor Detection Techniques
Abstract: Brain tumor is an abnormal growth of the cells inside the brain. Detecting brain tumor takes special skills and techniques because they are difficult to detect – especially in early stages. The boundary of the tumor (i.e., the abnormality in brain) in an MRI or different medical images can be traced using image processing techniques. The input image to the system is taken either from the available database or the …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 1, Issue 3, 2014 · pp. 6–9 Read article
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Data Mining Methods for Terrorist Activity
Abstract: ABSTRACTIdentification of outliers is an important component of data mining since such observations can have a profound influence and distort the analysis. In the recent years, detection of outlier has been broadly applied in the field of data mining. It is an important method for many research applications such as credit card fraud, computer intrusion detection, and criminal activities in electronic commerce, medical diagnosis and anti-terrorism, image processing, etc. Detection …
Published in Journal Of Network security · Vol. 5, Issue 3, 2017 · pp. 17–22 Read article
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Data Mining Methods for Terrorist Activity
Abstract: Identification of outliers is an important component of data mining since such observations can have a profound influence and distort the analysis. In the recent years, detection of outlier has been broadly applied in the field of data mining. It is an important method for many research applications such as credit card fraud, computer intrusion detection, and criminal activities in electronic commerce, medical diagnosis and anti-terrorism, image processing. Detection of …
Published in Research & Reviews : Journal of Statistics · Vol. 8, Issue 1, 2019 · pp. 38–43 Read article
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Convolutional Neural Network and its Architectures
Abstract: Convolutional neural network (CNN) is a type of artificial neural network (ANN) with multiple layers. From the past decades, it has been considered as a powerful classification technique as it can handle a huge amount of imagery data. It can be applied in the field of image recognition. The name CNN has been derived from the mathematical linear operation known as convolution which is performed between two matrices. CNN has …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 2, 2021 · pp. 6–14 Read article
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Fuzzy Logic in Image Processing: Definition and Scheme
Abstract: Digital image processing is a evergreen developing and energetic location with petition bust out into habitual existence likewise medicinal drug, area evaluation, inspection, support, automatic enterprise inspection and plenty extra zone. The advanced gadget especially makes a specialty of a fuzzy logic structures in an image processing. The most important subject of device is about to illustrate the application of Fuzzy common sense in photograph transforming with a short measure …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 3, 2021 · pp. 29–33 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Sensors based Human Visual System: e-Retina
Abstract: This study explores the potential of bio-inspired sensor design to replicate the adaptive and highly efficient nature of the human visual system and e-retina. This study presents a novel sensor array incorporating foveated vision principles and dynamic range adaptation mechanisms. Our study demonstrates the improved performance of this system in complex visual scenes, particularly in low illumination and high-contrast scenarios. This study highlights the advantages of mimicking biological principles in …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 1, 2025 · pp. 14–22 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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MedVerse AI: An Intelligent Digital Health Platform for Patient-Centric Healthcare and Proactive Disease Prediction
Abstract: The rapid digitization of healthcare has led to an unprecedented growth in medical data, ranging from diagnostic images and laboratory reports to electronic health records and clinical notes. Despite this abundance, patients and healthcare providers often struggle to extract meaningful insights due to data complexity and fragmentation. MedVerse AI proposes an intelligent digital health platform that unifies medical image analysis, clinical report interpretation, real-time interaction, and predictive disease analytics into …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 2, 2026 · pp. 1–7 Read article
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Medical Healthcare Applications
Abstract: Medical imaging may be a heatedly contested field wherever winning merchandise maximize healthcare price by providing the simplest pictures within the shortest quantity of your time to assure correct designation and treatment for patients whereas maximizing the potency of workers and facilities. The advancement of medical imaging has resulted in terribly giant knowledge sets and progressively advanced algorithms golf stroke ever-growing demands on process power and gap plenty of opportunities …
Published in Research and Reviews: A Journal of Medicine · Vol. 9, Issue 3, 2019 · pp. 35–38 Read article
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Intelligent Brain Tumor Diagnosis with AI-Based Classification* * Harnessing Deep and Machine Learning for Tumor Identification
Abstract: Brain tumors have become a leading cause of cancer- related deaths, posing significant health risks to many patients. This urgent medical challenge calls for rapid, automated, and reliable techniques to detect brain tumors accurately. Timely and precise tumor identification is crucial for devising effective medical plans that have the potential to save lives and improve patient outcomes. By leveraging advanced image processing methods, healthcare professionals can enhance their diagnostic capabilities …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
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Brief Review of Medical Image Fusion Techniques Based on Hybrid Intelligence
Abstract: An image fusion combines complementary images from multiple images such that the fused image is more suitable for further processing tasks or specific application. The goal of image fusion is to integrate complementary multi sensor, multi temporal and/or multi view data into a new image containing more information for proper medical diagnosis and different application tasks. The purpose of this paper is a survey of image fusion algorithms based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 3, Issue 1, 2016 · pp. 8–15 Read article
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Lung Cancer Detection and Classification Using Deep Learning
Abstract: Lung cancer is a disease that can be effectively treated if detected early. Various technologies, such as magnetic resonance imaging, isotopes, X-rays, and computed tomography scans, are employed for diagnosis. One of the most crucial strategies in combating cancer is early detection, which greatly enhances a patient’s likelihood of survival; this is where artificial intelligence plays a significant role. The approach proposed in this study leverages historical medical data to …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 3, 2024 · pp. 11–17 Read article
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Nail Image Processing for Early Symptom Detection of Diseases based on Supervised Learning
Abstract: Digital Image Processing of human nail can be used for the prediction of various systemic and dermatological diseases. The proposed system – Nail Image Processing System using SVM (NIPS-S) helps us to create a model for the analysis of human nail and predict various diseases. The input to the proposed system is the Human Palm Image. The nail portion is segmented and a combination of nail color, shape and texture …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 3, 2017 · pp. 49–61 Read article
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Application of Image Denoising through Comorbid Pixel Regularization Algorithm based on Neuro-Fuzzy Rule
Abstract: This study presents a novel approach of image denoising for medical images. Since, for medical diagnosis, action of object extraction plays a vital role but such jobs are limited with the visual observation and there is no denying from the fact that the medical images are subjected to noise which makes it difficult for the medical practitioner to extract features from such noisy images. Therefore, for accurate decisions it is …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 2, Issue 2, 2014 · pp. 7–11 Read article
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Image Enhancement Using Super Resolution Technique
Abstract: AbstractThe proposed super resolution technique finds it’s applicability in reconstructing a distorted image to a higher resolution image. The photographs consisting of the previous techniques were drawn towards lower force light which was considered to be a huge disadvantage. In view of this default, a novel strategy of Histogram. Equalisation is introduced and further detailed investigation is carried on. Light Enlightenment and picture quality is improved using the proposed technique. …
Published in Current Trends in Signal Processing · Vol. 10, Issue 2, 2020 · pp. 12–16 Read article
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Radiopaque Polymer Composites for Improved Visualization of Interventional Devices
Abstract: Radiopaque polymer composites are increasingly important for improving the visualization of interventional medical devices under X-ray and fluoroscopic imaging while maintaining the flexibility, mechanical performance, and processability required for minimally invasive applications. This narrative review summarizes recent developments in radiopaque polymer composites, with emphasis on radiopaque filler selection, polymer–filler interactions, processing strategies, structure–property relationships, biocompatibility, and device applications. A focused literature search was conducted using PubMed, Scopus, Web of Science, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article