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89 articles for “MRI image”
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Brain Tumor Detection Using RestNet50 Architecture
Abstract: This paper presents a novel deep learning model for brain tumor diagnosis from MRI scans on the basis of ResNet50 with some modifications. Optimizing the modified layers and pre-trained ResNet50 for improved diagnostic accuracy and reliability in real-world clinical settings is one of the key contributions of this paper. The model was trained on an extremely well-balanced data of 2,577 MRI scans, which were split equally among the tumor and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 1–13 Read article
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Identification and Categorization of Brain Tumors
Abstract: Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Strategic and well-thought-out treatment planning significantly contributes to improving a patient's overall quality of life. Many different imaging techniques, such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and also ultrasound are used to evaluate tumors in different parts of the body, with a focus on using MRI images for brain tumors. It is …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 2, 2023 · pp. 32–37 Read article
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Uncertainty Prediction in Brain Tumour Segmentation
Abstract: Gliomas are one of the most common brain tumour at different levels of the province, with Magnetic Resonance Imaging (MRI) used for diagnosis. In this project, It was asked to try to find uncertainty in the Brain Tumour Segmentation on MRI images using the BraTs19 Dataset and to look at how machine learning algorithms can work with these MRI images. Since these tissues are so large in shape and appearance, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 13, Issue 2, 2023 · pp. 40–52 Read article
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Development and Evaluation of Polymer-based Educational Materials for Reducing Anxiety During MRI Scans
Abstract: Magnetic Resonance Imaging (MRI) scans are crucial diagnostic tools, but patient anxiety can hinder successful completion of the procedure. This study investigates the design, development, and evaluation of educational materials fabricated from polymers for use in reducing anxiety in patients undergoing MRI scans. We aimed to create informative and user-friendly materials using polymers due to their potential advantages, such as durability, visual appeal, and ease of disinfection. The educational materials …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 119–124 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Brain Tumor Detection Using Image Processing
Abstract: Brain tumor means the aggregation of abnormal cells in some tissues of the brain. Brain tumor can be cancerous or noncancerous. The most common types of brain tumors are Glioma, Meningioma and Pituitary tumor. Early detection of tumor cells is essential in-patient treatment and recovery. A brain tumor is typically diagnosed through a lengthy and complicated process. The MRI images of various patients at various stages can be used for …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 2, 2022 · pp. 8–14 Read article
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Posterior Reversible Encephalopathy Syndrome Secondary to Management of Dimorphic Anemia by Repeated Blood Transfusions: A Case Report
Abstract: Posterior reversible encephalopathy syndrome, popularly known asPRES, is defined as a clinicoradiological syndrome which is characterized by symptoms such as headache, seizures, and altered consciousness and characterized by white matter vasogenic edema affecting the posterior occipital and parietal lobes of the brain .We report a 39-year-old woman who was treated by iron and blood transfusion for dimorphic anemia with a hemoglobin (Hb) level of 2 g/dl. Patient developed three episodes …
Published in Research and Reviews: A Journal of Medicine · Vol. 8, Issue 2, 2018 · pp. 6–8 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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Imaging Technologies in Breast Cancer Screening Beyond Mammography
Abstract: There is a passionate debate in medical world about the best screening method for breast cancer. Early detection is an effective way to diagnose and manage breast cancer. Mammography is the most widely used screening modality, with solid evidence of benefit for women aged 40 to 74 years. Even then it has also undergone increased scrutiny for false-positives with additional testing which increase radiation dose, cost and anxiety. False-negatives with …
Published in Journal of Advances in Shell Programming · Vol. 7, Issue 1, 2020 · pp. 22–32 Read article
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Automatic Detection and Classification of Brain Tumor in Magnetic Resonance Images
Abstract: Brain tumor is one of the serious diseases that have caused death to many people in recent years. The complex structure of the brain and its main function associated with the central nervous system and its critical role in controlling most of the functions of the body make detection of tumor a challenging task. Many techniques have been presented in the medical field in order to detect brain tumor from …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 5, Issue 2, 2018 · pp. 34–40 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 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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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 Read article
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Comparative Analysis of Proposed FCM Clustering Integrated Enhanced Firefly-Optimized Algorithm (En-FAOFCM) for MR Image Segmentation and Performance Evaluation
Abstract: Image segmentation has a significant responsibility in diagnosis and treatment of diseases. To scan patients and determine the severity of certain injuries in hospitals, magnetic resonance imaging (MRI) method is normally used. This paper emphasizes on comparative study of segmentation techniques for segmenting MRI brain images. In this regard, to group the pixels of images in the intensity space, unsupervised clustering techniques are used. Here enhanced firefly algorithm is used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 1, 2016 · pp. 32–44 Read article
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A Review on Detection of Autism Spectrum Disorder Using Signal Processing
Abstract: AbstractAutism is a neural developmental disability associated with impairments in communication and social interaction; it can be detected by various methods such as Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG). MRI is a technique which captures the image of various sections of brain. It is categorised as structural MRI (sMRI) and functional MRI (fMRI). The detection involves capturing the image, removing the unwanted regions of brain, segmenting the images and …
Published in Current Trends in Signal Processing · Vol. 8, Issue 2, 2018 · pp. 12–24 Read article
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A Comparison Study of Different Classification Algorithm on Brain Tumor Segmentation
Abstract: A brain tumor is a tissue mass caused by aberrant cell proliferation in the brain. It is a collection of tissues that causes hormonal alterations and eventually death. In order to save human lives, brain tumors prognosis and prevention is a difficult task. The use of modern medical image processing approaches has made the identification of brain tumors more flexible in recent years. Due to the absence of ionizing radiations, …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 3, 2021 · pp. 1–7 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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A Review on MR Brain Image Segmentation Based on Different Techniques
Abstract: In past few years, the growth in Magnetic Resonance Imaging (MRI) provided a new way to detect and diagnose the brain related problems such as Alzheimer, schizophrenia and brain tumor. Many supervised and unsupervised techniques are available for image segmentation. In medical field supervised and unsupervised segmentation both are available but unsupervised is in more demand then supervised because it requires external assistance. Whereas unsupervised segmentation reflects better results. In …
Published in Journal of Operating Systems Development & Trends · Vol. 2, Issue 2, 2015 · pp. 9–14 Read article
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A Multimodal Image Fusion based on NonSubsampled Contourlet Transform and Sparse Representation
Abstract: Detection of tumors in the brain is vital in diagnosis of brain cancer. Doctors suggest numerous scans like CT, MRI, PET, and SPECT for estimating the type of cancer, size and location of the tumor and the aging or spread of cancer. A single imaging technique is not sufficient for correct diagnosis of the disease. In case the scans are ambiguous, it can lead doctors to incorrect diagnosis, which can …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 2, 2018 · pp. 12–21 Read article