AIMC Topic: Cerebrovascular Circulation
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QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping.
Magnetic resonance in medicine
Oct 31, 2021
PURPOSE: To improve accuracy and speed of quantitative susceptibility mapping plus quantitative blood oxygen level-dependent magnitude (QSM+qBOLD or QQ) -based oxygen extraction fraction (OEF) mapping using a deep neural network (QQ-NET).
Computed Tomography Perfusion-Based Prediction of Core Infarct and Tissue at Risk: Can Artificial Intelligence Help Reduce Radiation Exposure?
Stroke
Oct 21, 2021
BACKGROUND AND PURPOSE: We explored the feasibility of automated, arterial input function independent, vendor neutral prediction of core infarct, and penumbral tissue using complete and partial computed tomographic perfusion data sets through neural ...
AIFNet: Automatic vascular function estimation for perfusion analysis using deep learning.
Medical image analysis
Aug 6, 2021
Perfusion imaging is crucial in acute ischemic stroke for quantifying the salvageable penumbra and irreversibly damaged core lesions. As such, it helps clinicians to decide on the optimal reperfusion treatment. In perfusion CT imaging, deconvolution ...
Deep-learning-based attenuation correction in dynamic [O]HO studies using PET/MRI in healthy volunteers.
Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Jul 11, 2021
Quantitative [O]HO positron emission tomography (PET) is the accepted reference method for regional cerebral blood flow (rCBF) quantification. To perform reliable quantitative [O]HO-PET studies in PET/MRI scanners, MRI-based attenuation-correction (M...
Deep learning-based identification of acute ischemic core and deficit from non-contrast CT and CTA.
Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Jun 8, 2021
The accurate identification of irreversible infarction and salvageable tissue is important in planning the treatments for acute ischemic stroke (AIS) patients. Computed tomographic perfusion (CTP) can be used to evaluate the ischemic core and deficit...
A Machine Learning Approach to First Pass Reperfusion in Mechanical Thrombectomy: Prediction and Feature Analysis.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Apr 19, 2021
INTRODUCTION: Novel machine learning (ML) methods are being investigated across medicine for their predictive capabilities while boasting increased adaptability and generalizability. In our study, we compare logistic regression with machine learning ...
Prediction of cerebral perfusion pressure during CPR using electroencephalogram in a swine model of ventricular fibrillation.
The American journal of emergency medicine
Feb 25, 2021
BACKGROUND: Measuring the quality of cardiopulmonary resuscitation (CPR) is important for improving outcomes in cardiac arrest. Cerebral perfusion pressure (CePP) could represent cerebral circulation during CPR, but it is difficult to measure non-inv...
Cerebral blood flow measurements with O-water PET using a non-invasive machine-learning-derived arterial input function.
Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Feb 8, 2021
Cerebral blood flow (CBF) can be measured with dynamic positron emission tomography (PET) of O-labeled water by using tracer kinetic modelling. However, for quantification of regional CBF, an arterial input function (AIF), obtained from arterial bloo...
Machine learning-based multimodal prediction of language outcomes in chronic aphasia.
Human brain mapping
Dec 30, 2020
Recent studies have combined multiple neuroimaging modalities to gain further understanding of the neurobiological substrates of aphasia. Following this line of work, the current study uses machine learning approaches to predict aphasia severity and ...
Language Tests
Aphasia
Outcome Assessment, Health Care
Neuroimaging
Cerebrovascular Circulation
Diffusion Tensor Imaging
Multimodal Imaging
Chronic Disease
Stroke
Severity of Illness Index
Functional Neuroimaging
Support Vector Machine
Humans
Aged, 80 and over
Magnetic Resonance Imaging
Female
Adult
Aged
Male
Middle Aged
Multi-band MR fingerprinting (MRF) ASL imaging using artificial-neural-network trained with high-fidelity experimental data.
Magnetic resonance in medicine
Oct 26, 2020
PURPOSE: We aim to leverage the power of deep-learning with high-fidelity training data to improve the reliability and processing speed of hemodynamic mapping with MR fingerprinting (MRF) arterial spin labeling (ASL).
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