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Supplementary_Table_1 – Supplemental material for An update on magnetic resonance imaging markers in AD

Michela Leocadi, Elisa Canu, Davide Calderaro, Davide Corbetta, Massimo Filippi, Federica Agosta
2020 Figshare  
Supplemental material, Supplementary_Table_1 for An update on magnetic resonance imaging markers in AD by Michela Leocadi, Elisa Canu, Davide Calderaro, Davide Corbetta, Massimo Filippi and Federica Agosta  ...  ., 2018 67 244 HC 241 AD T1-weighted sequences. Techniques: predictive model computerized tool.  ...  magnetic resonance imaging; SCD=subjective cognitive decline; SD=single-domain; sMCI=stable mild cognitive impairment; SN=salience network; SPARE-AD=Spatial Pattern of Abnormality for Recognition of Early  ... 
doi:10.25384/sage.12922349.v1 fatcat:vc6pb2kqdnfzxk2vni3uhf4mvq

Texture Analysis of T1-Weighted and Fluid-Attenuated Inversion Recovery Images Detects Abnormalities That Correlate With Cognitive Decline in Small Vessel Disease

Daniel J. Tozer, Eva Zeestraten, Andrew J. Lawrence, Thomas R. Barrick, Hugh S. Markus
2018 Stroke  
Texture analysis was performed on fluid-attenuated inversion recovery and T1-weighted images.  ...  The TP obtained from the SVD cohort were cross-sectionally compared with 54 age-matched controls scanned on the same magnetic resonance imaging system.  ...  Sources of Funding Disclosures None.  ... 
doi:10.1161/strokeaha.117.019970 pmid:29866751 pmcid:PMC6022812 fatcat:e65o3w3gbngsbnhr6gw777zrwi

Predicting intelligence based on cortical WM/GM contrast, cortical thickness and volumetry [article]

Juan Miguel Valverde, Vandad Imani, John D. Lewis, Jussi Tohka
2019 arXiv   pre-print
We propose a four-layer fully-connected neural network (FNN) for predicting fluid intelligence scores from T1-weighted MR images for the ABCD-challenge.  ...  These last two measurements were derived from the T1-weighted MR images using cortical surfaces produced by the CIVET pipeline.  ...  In this study, we used a supervised learning model to automatically predict fluid intelligence scores, i.e. fluid intelligence with demographic confounding factors removed, based on T1-weighted Magnetic  ... 
arXiv:1909.05660v1 fatcat:ljopr4dzive6jnpuu2tcppfmxu

Sex differences in predicting fluid intelligence of adolescent brain from T1-weighted MRIs [article]

Sara Ranjbar, Kyle W. Singleton, Lee Curtin, Susan Christine Massey, Andrea Hawkins-Daarud, Pamela R. Jackson, Kristin R. Swanson
2019 arXiv   pre-print
As part of the Adolescent Brain Cognitive Development Neurocognitive Prediction Challenge 2019, we sought to predict Gf in children aged 9-10 from T1-weighted (T1W) MRIs.  ...  Links to Gf have been found in magnetic resonance imaging (MRI) sequences such as functional MRI and diffusion tensor imaging.  ...  Magnetic resonance imaging (MRI) is a powerful tool for non-invasively visualization of the body's tissues.  ... 
arXiv:1908.02333v1 fatcat:p7sdkjmicbhbpjzcsfpapcl3fu

Predicting Intelligence Based on Cortical WM/GM Contrast, Cortical Thickness and Volumetry [chapter]

Juan Miguel Valverde, Vandad Imani, John D. Lewis, Jussi Tohka
2019 Lecture Notes in Computer Science  
We propose a four-layer fully-connected neural network (FNN) for predicting fluid intelligence scores from T1-weighted MR images for the ABCD-challenge.  ...  These last two measurements were derived from the T1-weighted MR images using cortical surfaces produced by the CIVET pipeline.  ...  In this study, we used a supervised learning model to automatically predict fluid intelligence scores, i.e. fluid intelligence with demographic confounding factors removed, based on T1-weighted Magnetic  ... 
doi:10.1007/978-3-030-31901-4_7 fatcat:z3mtbs2rurfwrm3vkhjcjhlr5a

Using Deep Learning to Detect Spinal Cord Diseases on Thoracolumbar Magnetic Resonance Images of Dogs

Anika Biercher, Sebastian Meller, Jakob Wendt, Norman Caspari, Johannes Schmidt-Mosig, Steven De Decker, Holger Andreas Volk
2021 Frontiers in Veterinary Science  
Magnetic resonance imaging (MRI) is the imaging modality of choice for many spinal cord disorders.  ...  The network was tested using 7,695 MR images from 125 dogs. The network performed best in detecting IVDPs on sagittal T1-weighted images, with a sensitivity of 100% and specificity of 95.1%.  ...  Development of a deep convolutional neural network to predict grading of canine meningiomas from magnetic resonance images. Vet J.  ... 
doi:10.3389/fvets.2021.721167 pmid:34796224 pmcid:PMC8593183 fatcat:s22o55asune3fd6wqh75hkqyf4

Editorial: Advanced Neuroimaging of Brain Metastases

Behroze A. Vachha, Susie Y. Huang, Tarik F. Massoud
2021 Frontiers in Neurology  
These methods include: black blood MRI; magnetic resonance spectroscopy; quantitative magnetization transfer imaging; dynamic contrast-enhanced MRI to measure the transmembrane water exchange rate; chemical  ...  Advanced magnetic resonance imaging (MRI) and positron emission tomography (PET) techniques are playing an increasingly important role in the surveillance, diagnosis, and management of patients with brain  ...  from computational fluid modeling using dynamic contrast-enhanced MRI, can predict long-term outcomes of lung cancer brain metastases treated using stereotactic radiosurgery.  ... 
doi:10.3389/fneur.2021.668310 pmid:33815266 pmcid:PMC8010233 fatcat:w5qeidq6p5bazaf7ovkr4qo6ie

Atypical presentation and a novel mutation in ALMS1: implications for clinical and molecular diagnostic strategies for Alström syndrome

S Taşdemir, A Güzel-Ozantürk, JD Marshall, GB Collin, RK Özgül, N Narin, M Dündar, JK Naggert
2013 Clinical Genetics  
JDM, GBC, and JKN are supported by the National Institutes of Health HD036878.  ...  The Jackson Laboratory Core Scientific Services, institutional multimedia, was supported by US PHS National Institutes of Health grant CA34196. We thank  ...  Structural magnetic resonance imaging (MRI) revealed prominent cerebellar hemisphere folium due to atrophy, and a mildly thin brain stalk in conventional sagittal T1-weighted and axial T2-weighted flair  ... 
doi:10.1111/j.1399-0004.2012.01883.x pmid:22533542 pmcid:PMC3777397 fatcat:gxlg6dmm6fblbcb636zubejhja

Novel Magnetic Resonance Imaging Tools for the Diagnosis of Degenerative Disc Disease: A Narrative Review

Carlo A. Mallio, Gianluca Vadalà, Fabrizio Russo, Caterina Bernetti, Luca Ambrosio, Bruno Beomonte Zobel, Carlo C. Quattrocchi, Rocco Papalia, Vincenzo Denaro
2022 Diagnostics  
With its capacity to accurately characterize intervertebral disc (IVD) and spinal morphology, magnetic resonance imaging (MRI) has been established as one of the most valuable tools in diagnosing DDD.  ...  of the degenerative process rather than intervene at the latest stages of the disease.  ...  Na-MRI-sodium magnetic resonance imaging; ADC-apparent diffusion coefficient; DTI-diffusion tensor imaging; dGEMRIC-delayed gadolinium-enhanced MRI of cartilage; DWI-diffusion-weighted imaging; FAfractional  ... 
doi:10.3390/diagnostics12020420 pmid:35204509 pmcid:PMC8870820 fatcat:7bi22rguvrekpc63lyyyg253nq

Application of Optimized Neural Network Models for Prediction of Nuclear Magnetic Resonance Parameters in Carbonate Reservoir Rocks

Javad Ghiasi-Freez, Amir Hatampour, Payam Parvasi
2015 International Journal of Intelligent Systems and Applications  
Nuclear magnetic resonance (NMR) log measures some of the most useful characteristics of reservoir rock; the capabilities of the optimized models were used for prediction of nuclear magnetic resonance  ...  This strategy was capable of significantly improving the accuracy of a neural network by optimizing network parameters such as weights and biases.  ...  ACKNOWLEDGMENT The authors would like to appreciate Islamic Azad University of Dashtestan for providing the technical and financial supports of this research.  ... 
doi:10.5815/ijisa.2015.06.02 fatcat:6hmw7jcm6jdztfkwfqki2eq2we

Reverse Engineering Glioma Radiomics to Conventional Neuroimaging

Manabu KINOSHITA, Yonehiro KANEMURA, Yoshitaka NARITA, Haruhiko KISHIMA
2021 Neurologia medico-chirurgica  
A novel radiological research field pursuing comprehensive quantitative image, namely "Radiomics," gained traction along with the advancement of computational technology and artificial intelligence.  ...  At the same time, many significant insights were discovered through this research project, some of which could be "reverse engineered" to improve conventional non-radiomic MR image acquisition.  ...  .: Predicting deletion of chromosomal arms 1p/19q in low-grade Gliomas from MR images using machine intelligence.  ... 
doi:10.2176/nmc.ra.2021-0133 pmid:34373429 pmcid:PMC8443974 fatcat:i7mzjddf6rfbpknnwp4pirce34

A Combined Deep Learning-Gradient Boosting Machine Framework for Fluid Intelligence Prediction [chapter]

Yeeleng S. Vang, Yingxin Cao, Xiaohui Xie
2019 Lecture Notes in Computer Science  
The ABCD Neurocognitive Prediction Challenge is a community driven competition asking competitors to develop algorithms to predict fluid intelligence score from T1-w MRIs.  ...  These extracted features are then used to train a gradient boosting machine that predicts the residualized fluid intelligence score.  ...  In this endeavor, leaders of the study organized the ABCD Neurocognitive Prediction Challenge (ABCD-NP-Challenge 2019) [1] and invited teams to make predictions about fluid intelligence from T1-w magnetic  ... 
doi:10.1007/978-3-030-31901-4_1 fatcat:fuknspmndzay3oqchyghjaarcq

Prediction of Neuropsychological Impairment in Multiple Sclerosis

Ralph H. B. Benedict, Bianca Weinstock-Guttman, Inna Fishman, Jitendra Sharma, Christopher W. Tjoa, Rohit Bakshi
2004 Archives of Neurology  
Cognition and magnetic resonance imaging correlations are well established in patients with multiple sclerosis (MS), but it is unclear whether lesion burden or atrophy accounts for most of the predictive  ...  Correlations between neuropsychological tests and the following magnetic resonance imaging indices were considered: T1 hypointense lesion volume, fluidattenuated inversion recovery hyperintense lesion  ...  More recent magnetic resonance imaging (MRI) studies demonstrated an association between lesion burden and cognitive impairment.  ... 
doi:10.1001/archneur.61.2.226 pmid:14967771 fatcat:5pbiunh42bgcxgwnjktxp3ufta

Brain Tumor Image Segmentation in MRI Image

Hapsari Peni Agustin Tjahyaningtijas
2018 IOP Conference Series: Materials Science and Engineering  
Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors.  ...  There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field  ...  Four standard MRI modalities used for glioma diagnosis include T1-weighted MRI (T1), T2weighted MRI (T2), T1-weighted MRI with gadolinium contrast enhancement (T1-Gd) and Fluid Attenuated Inversion Recovery  ... 
doi:10.1088/1757-899x/336/1/012012 fatcat:mytlgkmsdra2hdmcj2hw4fnxk4

Stroke Mimics and Chameleons from the Radiological Viewpoint of Glioma Diagnosis

Ayaka SASAGAWA, Takeshi MIKAMI, Yusuke KIMURA, Yukinori AKIYAMA, Shintaro SUGITA, Tadashi HASEGAWA, Masahiko WANIBUCHI, Nobuhiro MIKUNI
2020 Neurologia medico-chirurgica  
Gliomas are sometimes difficult to differentiate from strokes and are often misdiagnosed on magnetic resonance imaging (MRI); thus, the terms "stroke mimics" and "stroke chameleons" have been introduced  ...  Stroke mimics group has a tendency to be higher rate of hyperintensity lesion on diffusion-weighted imaging (DWI) compared with stroke chameleons group.  ...  FLAIR: fluid-attenuated inversion recovery, DWI: diffusion-weighted imaging, MRI: magnetic resonance imaging.  ... 
doi:10.2176/nmc.oa.2020-0309 pmid:33390559 pmcid:PMC7905296 fatcat:pjq3tazi35epzjnt2v3t4r2opm
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