AIMC Topic: Blood Flow Velocity
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Quantifying Valve Regurgitation Using 3-D Doppler Ultrasound Images and Deep Learning.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 24, 2022
Accurate quantification of cardiac valve regurgitation jets is fundamental for guiding treatment. Cardiac ultrasound is the preferred diagnostic tool, but current methods for measuring the regurgitant volume (RVol) are limited by low accuracy and hig...
Fully-automated deep learning-based flow quantification of 2D CINE phase contrast MRI.
European radiology
Oct 29, 2022
OBJECTIVES: Time-resolved, 2D-phase-contrast MRI (2D-CINE-PC-MRI) enables in vivo blood flow analysis. However, accurate vessel contour delineation (VCD) is required to achieve reliable results. We sought to evaluate manual analysis (MA) compared to ...
Accelerated 4D-flow MRI with 3-point encoding enabled by machine learning.
Magnetic resonance in medicine
Oct 5, 2022
PURPOSE: To investigate the acceleration of 4D-flow MRI using a convolutional neural network (CNN) that produces three directional velocities from three flow encodings, without requiring a fourth reference scan measuring background phase.
Automation of sub-aortic velocity time integral measurements by transthoracic echocardiography: clinical evaluation of an artificial intelligence-enabled tool in critically ill patients.
British journal of anaesthesia
Aug 26, 2022
A novel approach based on machine learning analysis of flow velocity waveforms to identify unseen abnormalities of the umbilical cord.
Placenta
Jul 21, 2022
INTRODUCTION: A Doppler ultrasound (DUS) is essential for detecting blood flow abnormalities in the umbilical cord (UC). Any morphological abnormalities of the UC may lead to morbidity and stillbirth. Some abnormalities such as torsion, strictures an...
Deep learning-based velocity antialiasing of 4D-flow MRI.
Magnetic resonance in medicine
Apr 5, 2022
PURPOSE: To develop a convolutional neural network (CNN) for the robust and fast correction of velocity aliasing in 4D-flow MRI.
Effects of age, gender, and hemisphere on cerebrovascular hemodynamics in children and young adults: Developmental scores and machine learning classifiers.
PloS one
Feb 4, 2022
A constant blood supply to the brain is required for mental function. Research with Doppler ultrasonography has important clinical value and burgeoning potential with machine learning applications in studies predicting gestational age and vascular ag...
An Exploratory Study on the Relationship between Brachial Arterial Blood Flow and Cardiac Output.
Journal of healthcare engineering
Dec 23, 2021
BACKGROUND: We have obtained prospective clinical outcomes using the brachial artery largely, such as Korotkoff sound and vasomotor function measurement by ultrasound guidance to predict the prognosis of cardiovascular diseases. Very few reports on t...
Joint Deep-Learning-Enabled Impact of Holistic Care on Line Coagulation in Hemodialysis.
Journal of healthcare engineering
Dec 16, 2021
In order to investigate the impact of holistic care on line coagulation and safety in hemodialysis and to address limitations of the conventional ultrasound flow vector imaging (VFM) technique, which requires proprietary software to acquire raw Doppl...
Deep Learning Automated Background Phase Error Correction for Abdominopelvic 4D Flow MRI.
Radiology
Nov 30, 2021
Background Four-dimensional (4D) flow MRI has the potential to provide hemodynamic insights for a variety of abdominopelvic vascular diseases, but its clinical utility is currently impaired by background phase error, which can be challenging to corre...
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