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65 articles for “MRI imaging”
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A Short Review on Breast Fibroadenomas
Abstract: Breast Fibroadenomas are the most common type of benign breast lumps found mainly in adolescent women. These are unilateral, smooth, demarcated, rubbery, mobile, and painless masses. They are believed to be formed by the influence of changes in the female reproductive hormone, estrogen and sometimes the combination of both estrogen and progesterone which mainly occurs at the time of puberty. Fibroadenomas are mostly found in women till the age of …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 11, Issue 2, 2022 · pp. 8–14 Read article
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A Case of Low-Grade Fibromyxoid Sarcoma: A Rare Soft Tissue Sarcoma
Abstract: Sarcomas are heterogeneous group of tumours that can occur throughout the body. Approximately two third of soft tissue sarcomas (STS) arises in the extremities. These rare tumours accounts for less than 1% cancers in adults. Treatment algorithm for STS depends on tumour stage, site and histology. A 28-year-male patient presented with complaint of swelling over the right anterior aspect of leg since past six months. He had a history of …
Published in Research and Reviews : Journal of Surgery · Vol. 7, Issue 1, 2018 · pp. 1–4 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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Risk After Pediatric MRI Scanning: A Nation-Wide, Population Based Case-Control Study
Abstract: This paper investigates the potential association between pediatric MRI (Magnetic resonance imaging) exposure and the risk of developing childhood brain tumors, using action-wide, population-based and case-control methodology. The increasing use of MRI in pediatric healthcare has raised concerns about potential long-term health risks, including the risk of developing brain tumors. Detecting the presence or absence of brain tumor through traditional methods might require a lot of time as well as …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 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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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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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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Evaluation of Small Vessel Disease by Advanced Brain Imaging
Abstract: Studying and comprehending brain small vessel disease requires extensive imaging. Recent applications of cutting-edge brain imaging techniques have led to the discovery of several significant results. Diffusion-weighted MRI studies have demonstrated the diagnostic accuracy of using clinical features alone or in combination with CT scan results to identify small vessel disease as the underlying cause is suboptimal in patients with acute lacunar syndromes. Acute infarcts caused by small vessel disease …
Published in International Journal of Cheminformatics · Vol. 2, Issue 1, 2024 · pp. 15–19 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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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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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
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Alzheimer’s Disease Classification Based on Transfer Learning of New-CNN Model
Abstract: The long-term, irreversible brain disorder “Alzheimer’s disease (AD)” currently has no known cure. Nonetheless, current medications may impede their advancement. Globally, those over 65 are the primary population affected by Alzheimer’s disease. Accurate detection of this condition requires early diagnosis. Because there are so many people who come with an ailment, manual diagnosis by health specialists is laborious and prone to error. Early detection of AD is a difficult undertaking …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 16–23 Read article
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A Review on Segmentation Approaches for Brain Tumor Detection
Abstract: It is commonly said statement ‘the health is wealth’, so if you are healthy then everything is with you. Although everyone takes care of their health in their own ways but some diseases are not under the control of the human being.The “tumor” is one of the crucial diseases which is till now, out of control, in which brain tumor is again a serious issue. The most crucial job which …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 9, Issue 1, 2021 · pp. 6–12 Read article