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89 articles for “MRI image”
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Survey of Liver Disease Prediction Using Machine Learning
Abstract: Liver disease is one of the major causes of death in all over world that impacts the number of people around the world. Diagnosis of liver at early stages is crucial to reduce morality. As technology is growing in health care, machine learning significantly affects health care for predicting conditions at early stages. This study reviews the different approaches based on machine learning and deep learning to predict liver disease. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 30–38 Read article
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Recent Advances in Nanobiotechnology: Applications and Future Perspectives
Abstract: Nanobiotechnology is a rapidly growing field that combines the principles of nanotechnology with biology, medicine, and biotechnology. This review article provides an overview of recent advances in nanobiotechnology and their applications in various fields, including drug delivery, imaging, biosensors, tissue engineering, and nanomedicine. The article also discusses the challenges and future prospects of nanobiotechnology. This review article provides an overview of recent advances in nanobiotechnology and their applications in various …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 24, Issue 3, 2022 · pp. 43–47 Read article
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A Comparative Machine Learning Framework for Early Prediction of Liver Cancer Using Clinical Attributes
Abstract: One of the main causes of cancer-related death globally is liver cancer, and improving patient outcomes depends heavily on early detection. However, low contrast, noise, organ similarity, and tumor shape and size variability make it difficult to accurately identify and segment liver tumors from medical imaging. Automated liver cancer diagnosis, segmentation, and prognosis have been greatly improved by recent developments in artificial intelligence (AI), especially deep learning. This work presents …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 39–47 Read article
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Analysis of Discrete Wavelet Transform for Denoising of Breast CT Image
Abstract: During acquisition of medical images noise gets induced in the digital image by various effects. The state of art devices used for capturing the images introduces complex type of addition noise in the images. No medical imaging devices are noise free. The most commonly used medical images are acquired from MRI (Magnetic Resonance Imaging), CT (Computed Tomography) and X-ray equipment’s. Additive noise into medical image decreases the visual quality that …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 7, Issue 1, 2018 · pp. 27–31 Read article
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Calculating SAR Distribution and RF Electromagnetic Field Due To MRI Coil at Human Model
Abstract: AbstractMRI (magnetic resonance imaging) is an effective method for diagnosis of diseases. The MRI system is made of some important units including RF (radio frequency) devices [1]. The RF coil is one of the important parts in the RF unit. During the imaging, the RF coil radiates EM (electromagnetic) pulse to the human body and in response receives the NMR (nuclear magnetic resonance) signals emitted from the nuclei, which constitutes …
Published in Journal of Communication Engineering & Systems · Vol. 3, Issue 2, 2013 · pp. 1–8 Read article
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Enhancement of Proton Density Weighted Magnetic Resonance Images using Singular Value Decomposition in Wavelet Domain
Abstract: Image enhancement techniques for low contrast medical images using Singular Value Decomposition (SVD) in Discrete Wavelet Transform domain (SVD-DWT) are proposed in the literature. However, shift sensitivity, poor directionality and a lack of phase information are the primary drawbacks of the discrete wavelet transform. This work introduces a novel method of image enhancement (SVD-SWT) using SVD in Stationary Wavelet Transform (SWT) to improve the contrast of Proton Density weighted Magnetic …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 10, Issue 2, 2022 · pp. 10–21 Read article
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Unravelling the Impact of AI: Insights into Pattern Recognition and Image Processing
Abstract: Apart from its academic origins, the evolution of Artificial Intelligence (AI) has emerged as a notable influence in shaping our daily experiences. Artificial intelligence, which focuses on domains such as image processing and pattern recognition, encompasses a vast array of topics, including its complex applications, obstacles, and societal repercussions. Machine Learning, Natural Language Processing, Computer Vision, Robotics, Expert Systems, Knowledge Representation, and AI Ethics are among the domains in which …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 1–7 Read article
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Toxicity of Copper Sulphate on Behaviour, Hematological and Biochemical Parameters of Mrigal Cirrhinus mrigala
Abstract: The present study deals with the toxicity of copper sulphate on behavior, hematological and biochemical parameters of Mrigal Cirrhinus mrigala. Copper sulphate was prepared and characterized by using SEM, FTIR and XRD. The physic-chemical characteristics of water sample were analyzed before the experiment. The sub-lethal analysis on Cirrhinus mrigala in different concentrations such as 10–40 and 50 ppm of copper sulphate were used for a period of 96 h. Based …
Published in Research and Reviews: A Journal of Toxicology · Vol. 11, Issue 1, 2024 · pp. 26–32 Read article
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Advances in Lung Cancer Detection and Diagnosis: An Integrative Approach Using Computational Chemistry, Statistics, Bioinformatics, Artificial Intelligence, and Machine Learning
Abstract: Lung cancer is still one of the most common and lethal cancers globally, accounting for more than a million deaths each year. Prompt detection is important, and imaging techniques like chest X-rays, MRIs, PETs, CTs, and molecular imaging have become important tools. But still, even though all these techniques do not provide an accurate classification of the lesion, they have led to the development of computer-based high-resolution image analysis. Computer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Detection and Classification of Alzheimer’s Disease Using Deep Learning Technique
Abstract: It is crucial that people with Alzheimer's disease (AD) receive a proper diagnosis to begin preventative action before irreparable brain damage develops. Most people who suffer from Alzheimer's disease (AD), a neurological condition that progresses, are older than 65. The area of interest (ROI) in the hippocampus has been extensively studied for several purposes, including neurological illness research, stress development monitoring, and memory function analysis. Moreover, a connection between Alzheimer's …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 15–20 Read article
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Horizons in Neuralgia Care: Addressing Unmet Needs and Future Prospects
Abstract: Neuralgia refers to intense, sharp, and often chronic pain resulting from damage or irritation to nerves. It is typically characterized by sudden, shooting pain along the course of a nerve, significantly impairing daily functioning and impacting both physical and emotional well-being. Given its intensity and chronic nature, neuralgia presents a complex challenge in clinical management, emphasizing the importance of timely diagnosis and effective intervention to improve patient outcomes. This comprehensive …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 1–8 Read article
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Segmentation Methods Applied on MR Medical Application
Abstract: AbstractImage segmentation techniques as applied in MRI of human brain are developing by leaps and bounds. The human brain is the most imaging design of the nature. Cancer and neurological problems are resolved using MR of the brain. The automatic diagnostic system starts with medical imaging, segmentation and analysis of the findings and then the final decisions which are further used to treat the patient. In the real world certain …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 3, 2016 · pp. 30–38 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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Polymer-Based Medical Restraints: Advances in Polymer Chemistry for Enhanced Patient Safety
Abstract: Medical restraints play a crucial role in ensuring patient and staff safety during medical procedures, particularly when dealing with individuals who may be at risk of self-harm or unintentional movement. Traditional restraints, often made from rigid materials or fabric straps, present several challenges, including patient discomfort, pressure injuries, and incompatibility with advanced medical imaging techniques such as MRI and CT scans. Moreover, traditional materials may deteriorate over time, diminishing their …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 153–157 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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Study on Brain Tumor Detection Using Morphological Operations in MATLAB with Graphical User Interface (GUI)
Abstract: Brain tumor detection plays a crucial role in early diagnosis and effective treatment planning. This research presents a MATLAB-based Graphical User Interface (GUI) for Brain Tumor Detection, incorporating a comprehensive pipeline of image processing techniques. The GUI provides a user-friendly platform, empowering medical professionals to accurately and efficiently analyze MRI brain scans. The GUI begins with text removal to eliminate any textual artifacts that may be present in the MRI …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 24–31 Read article
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Non -Invasive Ways to Detect Cancer
Abstract: Cancer is a diverse group of diseases characterized by uncontrolled cell growth and division, affecting millions worldwide and being a leading cause of death. The disease typically involves genetic alterations that disrupt the normal balance of cell growth, leading to the formation of tumors. Tumors can be benign, posing no threat as they do not spread, or malignant, capable of invading nearby tissues and metastasizing. There are more than 100 …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 59–67 Read article
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The Early Brain Hemorrhage Prediction System Using Machine Learning
Abstract: Brain hemorrhage is a critical medical emergency that requires immediate attention, as delays in diagnosis can result in severe neurological damage or death. The condition involves bleeding within or around brain tissues, leading to increased intracranial pressure and disruption of normal brain function. Although imaging techniques such as CT scans and MRI provide accurate diagnosis, their availability is limited in emergency and rural settings. In recent years, machine learning has …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 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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Role of Radiation Therapy in the Management of Mycosis Fungoides
Abstract: Cutaneous T-cell lymphoma (CTCL) consists of spectrum of diseases of which Mycosis Fungoides and Sézary's syndrome are most common. Mycosis Fungoides (MF) is a low-grade, chronic lymphoproliferative disorder affecting skin caused by abnormal proliferation of CD4 + T-cells. The incidence of MF is showing an increasing trend all over the world. Also, it is seen twice as often in males as in females (2:1) and mostly it occurs after fourth …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 1, Issue 1, 2012 · pp. 6–15 Read article