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13 articles for “Medical image fusion”
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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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A Novel Approach of Medical Image Fusion using Wavelet Transforms
Abstract: Image processing applications have been growing rapidly in real world. The term fusion means an approach to extract the useful information from several modalities. Image fusion (IF) is used to integrate the complementary information obtained from multisensor, multiview and/or multitemporal and get an image of more information and the quality of which cannot be achieved from any individual image. Different fusion algorithms are useful in many applications like medical diagnosis …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 1, 2018 · pp. 18–25 Read article
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Amalgamation of Medical Image using Wavelet Theory
Abstract: Image fusion has become a common term used within medical diagnostics and treatment. The term is used when multiple patient images are registered and overlaid or merged to provide additional information. Fused images may be created from multiple images from the same imaging modality, or by combining information from multiple modalities, such as magnetic resonance image (MRI), computed tomography (CT) etc. In radiology and radiation these images serve different purposes. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 2, Issue 1, 2015 · pp. 9–14 Read article
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Fusion of CT and MRI Scanned Medical Images Using Image Processing
Abstract: ABSTRACTIn the field of medicine, to evaluate or to examine the inner body parts, different radiometric scanning techniques can be used. Some most commonly used scanning techniques include the computerized tomography (CT) scan and magnetic resonance imaging (MRI) scan but the images of various body parts taken by using these scanning techniques have their own merits and demerits. MRI scans can show the images of soft tissues very clearly but …
Published in Journal of Computer Technology & Applications · Vol. 3, Issue 3, 2012 · pp. 17–20 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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Artificial Intelligence in Healthcare for Implants and Tissue Regeneration: Advances, Challenges, and Future Directions
Abstract: Artificial intelligence (AI) has been a revolutionary influence in contemporary healthcare, especially in implant design, biomaterials research, and tissue regeneration. In regenerative medicine, AI facilitates predictive modeling, optimization, and decision-making via the analysis of intricate biological, material, and clinical information. This study analyzes current research on AI applications in implant technologies and tissue regeneration, specifically addressing scaffold engineering, biomaterial characterisation, stem cell and gene treatments, smart biomaterials, and implant planning. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Advances in Deep Learning for Medical Image Analysis in the Era of Precision Medicine
Abstract: Medical imaging is fundamental to modern healthcare but analyzing the high-dimensional data requires advanced techniques. Manual image interpretation is time-consuming, subjective and limited in detecting complex patterns and minute details. Recent breakthroughs in Deep Learning offer transformative advances for unlocking clinically relevant information from medical images. This paper provides a comprehensive 6000+ word review of the current state-of-the-art Deep Learning techniques for medical image analysis including detailed coverage of key …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 2, 2023 · pp. 10–23 Read article
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Nuclear Diagnostic Imaging for PET Scan using Technetium-99m
Abstract: AbstractNuclear diagnostic procedures are used in almost every hospital worldwide on a daily basis. PET scan is the most commonly used nuclear medical imaging procedure. PET scan is considered a safer alternative to other nuclear diagnostic procedures. It is primarily used to identify the diseases, predict the possibility of occurrence of a particular disease, planning and analysis of a treatment. The PET scan has many applications but its only side …
Published in Journal of Nuclear Engineering & Technology · Vol. 8, Issue 2, 2018 · pp. 1–3 Read article
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Bioconjugates and Biohybrid Polymers: Intricate Cellular Integration Methods and Sophisticated Biofunctionalization Techniques for Tailored Properties in Medical Contexts
Abstract: Bioconjugates are made when biological molecules are covalently linked to manufactured polymers. They can be used in many ways for imaging, diagnosis, and specific drug delivery. Getting perfect cellular fusion is very important for how well they work. Biomolecules can be attached to polymer scaffolds in a controlled way using techniques like click chemistry and site-specific conjugation. This makes sure that the molecules connect optimally with their biological targets. Using …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 227–243 Read article
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Recent Advances in Content-based Image Retrieval: Techniques and Applications
Abstract: Content-based image retrieval (CBIR) plays a vital role in computer vision, driven by the increasing need for fast and accurate image retrieval across fields like healthcare, e-commerce, and digital libraries. This study offers a detailed review of CBIR methodologies, charting their progression from traditional feature extraction techniques, such as Local Binary Patterns (LBP), to contemporary deep learning-driven methods. The transformative impact of convolution neural networks (CNNs) is highlighted, emphasizing their …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 67–71 Read article
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Comprehensive Review of Adenoid Cystic Carcinoma: Pathogenesis, Diagnosis, and Emerging Therapeutic Approaches
Abstract: Adenoid cystic carcinoma (ACC)is an infrequent neoplasm, highly malignant, that develops mainly in the salivary glands with the potential to exist in any secretory glandular sites, including the lacrimal glands, breast, and respiratory tract. ACC usually has a benign initial course, but conversely, it is notoriously aggressive in behavior with high incidence of perineural invasion, local recurrence, and distant metastasis, mostly to the lungs. The tumor’s molecular features are characterized …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–17 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Sensor Technologies in Robotics: A Review of Vision, Tactile, and Proximity Sensing Systems
Abstract: Robotics has undergone remarkable advancements in recent decades, largely driven by the integration of cutting-edge sensor technologies. Sensors serve as crucial for allowing robots to precisely logic, interpret, and react to the world around them. Among the most essential sensor types used in robotics are vision sensors, tactile sensors, and proximity sensors. These technologies strengthen a robot’s capacity for successful navigation, for example, object manipulation, and contact with people and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 31–37 Read article