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24 results for “Brain Imaging”
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Research ArticleOpen accessEvery word in the titleWavelet Statistical Texture Features with Orthogonal Operators Tumour Classification in Magnetic Resonance Imaging BrainR. Meenakshi, P. AnandhakumarTumors medically also called neoplasms are an abnormal mass of tissue resulting from uncontrolled proliferation or division of cells occurring in the human body. If such growth is located in the brain then it is called as brain tumor. Identification of such tumors is a major challenge in the field of medical science. Early identification of tumors prove to be … …American Journal of Applied Sciences, Vol. 10, Issue 10 · 5 Sep 2013 · 6,600 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMorphological Aspects of the Inferior Frontal Gyrus and its Relations with Brain Hemispheres and Gender: A Study with in vivo Magnetic Resonance ImagingSergio Murilo Georgeto, Munir Antônio Gariba, Luiz Roberto AguiarThis study aims to evaluate the reliability of an anatomy-topographic location method for the anatomical references that form the inferior frontal gyrus and compare the findings of both studied brain hemisphere as well as the genre. Two different pulse sequences-gradient-echo T1 (T1 GRE) and reversal recovery gradient-echo T1 (T1 IR GRE) were used for such purpose. The sample consisted of … …Neuroscience International, Vol. 7, Issue 1 · 22 Mar 2017 · 7,272 accessesView PDFCite
Review ArticleOpen accessIn the keywordsProgress and Challenges of Neuroscience and Brain-inspired Artificial IntelligenceLidong Wang, Cheryl Ann AlexanderNeuroscience and brain-inspired artificial intelligence are significant research areas. Many countries have launched brain-related projects in which neuroscience and brain-inspired artificial intelligence are major targeted areas to increase national interests and enhance their strength in key areas such as military and homeland security in the competitive global world. Methods, emerging technologies, and progress in neuroscience and brain-inspired artificial intelligence are … …Neuroscience International, Vol. 11, Issue 1 · 4 Feb 2020 · 7,835 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCascaded MNetV3UNet: A Lightweight Two-Stage Architecture for High-Precision Brain Tumor Segmentation in MRIMayuri Popat, Sanskruti PatelPrecise brain tumor segmentation is an essential but quite challenging process in MRI images because of their irregular shapes, heterogeneous appearance, and low contrast with surrounding tissues. While U-Net-based architectures have achieved significant success, their high computational complexity limits deployment on resource-constrained systems. In this study, a Novel two-stage cascaded architecture, MNetV3UNet, is introduced, which employs the light-weight MobileNetV3-Large as … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,788 accessesView PDFCite
Clinical ProcedureOpen accessIn the keywordsThe Ruggiero-Klinghardt (RK) Protocol for the Diagnosis and Treatment of Chronic Conditions with Particular Focus on Lyme DiseaseDietrich Klinghardt, Marco RuggieroHere we describe the Ruggiero-Klinghardt (RK) Protocol that is based on integration of Autonomic Response Testing (ART) with diagnostic ultrasonography and on application of therapeutic ultrasounds; the latter are used as a provocation tool and as an instrument to optimize drug uptake and utilization in specific areas of the body. This protocol consists of a precise sequence of diagnostic and … …American Journal of Immunology, Vol. 13, Issue 2 · 8 Mar 2017 · 37,244 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCOMPUTER AIDED SEGMENTATION OF BRAIN TISSUES USING SOFT COMPUTING TECHNIQUESD. Ramkumar, I. Jacob Raglend, K. BatriIn this study, an efficient computer aided classification of brain tissue in to Gray Matter (GM), White Matter (WM) and Cerebro-Spinal Fluid (CSF) is proposed. The proposed work consists of the following sub blocks like denosing, feature extraction and Classifier. This initial partition is performed by ANFIS after extracting the textural features like local binary pattern and histogram features. The … …American Journal of Applied Sciences, Vol. 11, Issue 6 · 17 Apr 2014 · 6,662 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Brain MR Image Quality Using CNN With Best Denoising Modality for Improved Diagnosis of Abnormality: An AppraisalKavery Verma, Subodh Srivastava, Ritesh Kumar MishraDigital medical images acquired from the brain are highly susceptible to noise, which causes significant challenges for radiologists to identify abnormalities in a precise manner. Noise interference hampers both diagnostic accuracy and the interpretation of underlying abnormalities, potentially leading to flaw conclusions. Magnetic Resonance (MR) imaging is the most preferred digital imaging technique for brain abnormality detection. To achieve precise … …Journal of Computer Science, Vol. 22, Issue 3 · 26 Mar 2026 · 1,462 accessesView PDFCite
Research ArticleOpen accessIn the abstractMorphological Changes in Brain Tissue During Experimental HypoxiaAizhan Mussayeva, Ulbossin Kozhaniyazova, Laura Koibasova et al.The extensive application of hypoxic training to enhance cerebral circulation highlights its significant role in effectively realizing the therapeutic and health-promoting benefits of this method. The discrepancy between the data on the features of cerebral circulation and cellular metabolism in brain tissues during circulatory hypoxia and significant interest in the physiological patterns of the integrative response of the body determined … …OnLine Journal of Biological Sciences, Vol. 25, Issue 4 · 20 Feb 2026 · 1,552 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 abstractImproved Classification Model using CNN for Detection of Alzheimer’s DiseaseRagavamsi Davuluri, Ragupathy RengaswamyAlzheimer’s Disease (AD) is commonly called a neurodegenerative disorder and it is a common form of dementia. There is no permanent cure for this brain disease hence the early diagnosis of such disease using medical imaging system is highly significant. Machine learning models play a vital role in the detection of AD. Since most of the conventional machine learning models … …Journal of Computer Science, Vol. 18, Issue 5 · 30 May 2022 · 6,252 accessesView PDFCite