AIMC Topic: Cerebrovascular Circulation

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Predicting O-Water PET cerebral blood flow maps from multi-contrast MRI using a deep convolutional neural network with evaluation of training cohort bias.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism Nov 13, 2019
To improve the quality of MRI-based cerebral blood flow (CBF) measurements, a deep convolutional neural network (dCNN) was trained to combine single- and multi-delay arterial spin labeling (ASL) and structural images to predict gold-standard O-water ...
Reproducibility of Results Humans Aged Neural Networks, Computer Young Adult Adult Magnetic Resonance Imaging Male Models, Biological Data Analysis Positron-Emission Tomography Algorithms Middle Aged Cerebrovascular Circulation Brain Adolescent Oxygen Radioisotopes Female Water Image Processing, Computer-Assisted
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Temporally downsampled cerebral CT perfusion image restoration using deep residual learning.

International journal of computer assisted radiology and surgery Oct 31, 2019
PURPOSE: Acute ischemic stroke is one of the most causes of death all over the world. Onset to treatment time is critical in stroke diagnosis and treatment. Considering the time consumption and high price of MR imaging, CT perfusion (CTP) imaging is ...
Deep Learning Image Processing, Computer-Assisted Stroke Humans Brain Ischemia Neural Networks, Computer Algorithms Tomography, X-Ray Computed Perfusion Imaging Signal-To-Noise Ratio Cerebrovascular Circulation
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Estimation of cerebral blood flow velocity during breath-hold challenge using artificial neural networks.

Computers in biology and medicine Oct 17, 2019
UNLABELLED: The effect of untreated Obstructive Sleep Apnoea (OSA) on cerebral haemodynamics and CA impairment is an active field of research interest. A breath-hold challenge is usually used in clinical and research settings to simulate cardiovascul...
Female Adult Male Photoplethysmography Sleep Apnea, Obstructive Humans Neural Networks, Computer Blood Flow Velocity Cerebrovascular Circulation Models, Cardiovascular Breath Holding
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Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD.

Magnetic resonance in medicine Jul 4, 2019
PURPOSE: To apply an artificial neural network (ANN) for fast and robust quantification of the oxygen extraction fraction (OEF) from a combined QSM and quantitative BOLD analysis of gradient echo data and to compare the ANN to a traditional quasi-New...
Positron-Emission Tomography Healthy Volunteers Gray Matter White Matter Brain Mapping Oxygen Oxygen Consumption Least-Squares Analysis Cerebrovascular Circulation Normal Distribution Humans Neural Networks, Computer Brain Computer Simulation Male Image Processing, Computer-Assisted Magnetic Resonance Imaging Female Adult
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Collateral Automation for Triage in Stroke: Evaluating Automated Scoring of Collaterals in Acute Stroke on Computed Tomography Scans.

Cerebrovascular diseases (Basel, Switzerland) Jun 19, 2019
Computed tomography angiography (CTA) collateral scoring can identify patients most likely to benefit from mechanical thrombectomy and those more likely to have good outcomes and ranges from 0 (no collaterals) to 3 (complete collaterals). In this stu...
Cerebrovascular Circulation Middle Cerebral Artery Computed Tomography Angiography Cerebral Angiography Collateral Circulation Patient Selection Automation Blood Flow Velocity Thrombectomy Predictive Value of Tests Triage Radiographic Image Interpretation, Computer-Assisted Stroke Humans Machine Learning Prognosis Clinical Decision-Making
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Classifying intracranial stenosis disease severity from functional MRI data using machine learning.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism May 8, 2019
Translation of many non-invasive hemodynamic MRI methods to cerebrovascular disease patients has been hampered by well-known artifacts associated with delayed blood arrival times and reduced microvascular compliance. Using machine learning and suppor...
Magnetic Resonance Angiography Cerebrovascular Circulation Moyamoya Disease Cerebral Angiography Humans Middle Aged Severity of Illness Index Female Case-Control Studies Young Adult Machine Learning Image Processing, Computer-Assisted Sensitivity and Specificity Brain
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Support vector machine-based multivariate pattern classification of methamphetamine dependence using arterial spin labeling.

Addiction biology Jan 9, 2019
Arterial spin labeling (ASL) magnetic resonance imaging has been widely applied to identify cerebral blood flow (CBF) abnormalities in a number of brain disorders. To evaluate its significance in detecting methamphetamine (MA) dependence, this study ...
Brain Young Adult Adult Cerebrovascular Circulation Humans Perfusion Imaging Spin Labels Support Vector Machine Male Magnetic Resonance Imaging Area Under Curve Case-Control Studies ROC Curve Methamphetamine Imaging, Three-Dimensional Amphetamine-Related Disorders
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An empirical evaluation of multivariate lesion behaviour mapping using support vector regression.

Human brain mapping Dec 13, 2018
Multivariate lesion behaviour mapping based on machine learning algorithms has recently been suggested to complement the methods of anatomo-behavioural approaches in cognitive neuroscience. Several studies applied and validated support vector regress...
Support Vector Machine Magnetic Resonance Imaging Models, Neurological Behavior Brain Mapping Bias Humans Algorithms Stroke Image Processing, Computer-Assisted Brain Diseases Cerebrovascular Circulation
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Optimal cerebral perfusion pressure via transcranial Doppler in TBI: application of robotic technology.

Acta neurochirurgica Sep 29, 2018
Individualized cerebral perfusion pressure (CPP) targets may be derived via assessing the minimum of the parabolic relationship between an index of cerebrovascular reactivity and CPP. This minimum is termed the optimal CPP (CPPopt), and literature su...
Cerebrovascular Circulation Brain Injuries, Traumatic Humans Robotics Ultrasonography, Doppler
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Brain State Decoding Based on fMRI Using Semisupervised Sparse Representation Classifications.

Computational intelligence and neuroscience Apr 19, 2018
Multivariate classification techniques have been widely applied to decode brain states using functional magnetic resonance imaging (fMRI). Due to variabilities in fMRI data and the limitation of the collection of human fMRI data, it is not easy to tr...
Magnetic Resonance Imaging Feasibility Studies Supervised Machine Learning Cerebrovascular Circulation Young Adult Humans Mental Processes Male Brain Time Factors Computer Simulation Image Processing, Computer-Assisted Female
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