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7 articles for “fMRI”
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Research ArticleOpen accessEvery word in the titleApplication of MultiScale Hidden Markov Modeling Wavelet Coefficients to fMRI Activation DetectionFangyuan Nan, Yaonan Wang, Xiaoping MaProblem Statement: The problem of detection of functional magnetic resonance images (fMRIs), that is, to decide active and nonactive regions of human brain from fMRIs is studied in this paper. fMRI research is finding and will find more and more applications in diagnosing and treating brain diseases like depression and schizophrenia. At its initial stage fMRI detection are pixel-wise methods, … …Journal of Mathematics and Statistics, Vol. 4, Issue 4 · 31 Dec 2008 · 7,546 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOn the Probability Density Function of the Test Statistic for One Nonlinear GLR Detector Arising from fMRIFangyuan NanRecently an important and interesting nonlinear generalized likelihood ratio (GLR) detector emerged in functional magnetic resonance imaging (fMRI) data processing. However, the study of that detector is incomplete: the probability density function (pdf) of the test statistic was draw from numerical simulations without much theoretical support and is therefore, not firmly grounded. This correspondence presents more accurate (asymptotic) closed form … …Journal of Mathematics and Statistics, Vol. 3, Issue 2 · 30 Jun 2007 · 7,106 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFunctional Neuroimaging in Dementia and other Amnesic Disorders: A Radiological ReviewLeonardo Caixeta, Renata Teles Vieira, Sergio Machado et al.Problem statement: The structural and functional neuroimaging have much to contribute to the cognitive neuroscience. Approach: We describe a radiological review of the major dementia syndromes and Mild Cognitive Impairment (MCI), included Alzheimer's disease, Lewy body dementia, Vascular dementia, Front temporal Lobar degeneration, Dementia associated with parkinsonism and other amnesic syndromes. Results: The different syndromes and diseases presenting with dementia … …Neuroscience International, Vol. 2, Issue 1 · 23 Nov 2011 · 7,495 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Vertical Stacking-Based Ensemble Deep Learning Model for Early Diagnosis of Alzheimer's Disease Using Multimodal MRI ScansParvatham Niranjan Kumar, Lakshmana Phaneendra MaguluriEarly detection of Alzheimer's Disease (AD) is crucial for timely interventions that can slow disease progression, enhance quality of life, and assist with future planning. Convolutional Neural Networks (CNNs) are an efficient method for processing image-based data. In this work, we used CNN-based deep learning models to extract structural information from structural MRI (sMRI) and brain neuron connectivity patterns from … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 3,099 accessesView PDFCite
Research ArticleOpen accessIn the abstractAI-Based Feature Extraction Approaches for Dual Modalities of Autism Spectrum Disorder NeuroimagesMeenakshi Malviya, Chandra J, Nagendra NHigh-dimensional data, lower detection accuracy, susceptibility to manual errors, and the requirement of clinical experts are some drawbacks of conventional classification models available for Autism Spectrum Disorder (ASD) detection. To address these challenges and explore the affiliated information from advanced imaging modalities such as Magnetic Resonance Imaging (MRI) in structural MRI (sMRI) and resting state-functional MRI (rs-fMRI), the study applied … …Journal of Computer Science, Vol. 20, Issue 11 · 28 Sep 2024 · 5,087 accessesView PDFCite
Research ArticleOpen accessIn the abstractExperimental Evaluation of Adaptive Step-Size Based FxLMS Approach for Active Noise Control in Magnetic Resonance Imaging SystemsI. Juvanna, Uppu Ramachandraiah, G. Muthukumaran et al.Magnetic Resonance Imaging (MRI) scanners emit up to 135 decibels of acoustic noise, which is a major source of discomfort for patients and personnel evaluating them during routine medical scans, necessitating the development of a method to reduce the acoustic noise generated during MRI testing. The goal of this study is to propose a frequency-domain Active Noise Control (ANC) method … …Journal of Computer Science, Vol. 18, Issue 12 · 24 Nov 2022 · 5,503 accessesView PDFCite
Research ArticleOpen accessIn the abstractFPGA-Based Architecture for a Generalized Parallel 2-D MRI Filtering AlgorithmSami Hasan, Said Boussakta, Alex YakovlevProblem statement: Current Neuroimaging developments, in biological research and diagnostics, demand an edge-defined and noise-free MRI scans. Thus, this study presents a generalized parallel 2-D MRI filtering algorithm with their FPGA-based implementation in a single unified architecture. The parallel 2-D MRI filtering algorithms are Edge, Sobel X, Sobel Y, Sobel X-Y, Blur, Smooth, Sharpen, Gaussian and Beta (HYB). Then, the … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 4 · 20 Feb 2012 · 8,021 accessesView PDFCite