AIMC Topic: Heart Ventricles
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Automated Left Ventricular Dimension Assessment Using Artificial Intelligence Developed and Validated by a UK-Wide Collaborative.
Circulation. Cardiovascular imaging
May 17, 2021
BACKGROUND: requires training and validation to standards expected of humans. We developed an online platform and established the Unity Collaborative to build a dataset of expertise from 17 hospitals for training, validation, and standardization of s...
Multiscale attention guided U-Net architecture for cardiac segmentation in short-axis MRI images.
Computer methods and programs in biomedicine
May 4, 2021
BACKGROUND AND OBJECTIVE: Automatic cardiac segmentation plays an utmost role in the diagnosis and quantification of cardiovascular diseases.
Myocardial Function Imaging in Echocardiography Using Deep Learning.
IEEE transactions on medical imaging
Apr 30, 2021
Deformation imaging in echocardiography has been shown to have better diagnostic and prognostic value than conventional anatomical measures such as ejection fraction. However, despite clinical availability and demonstrated efficacy, everyday clinical...
Echocardiographic image multi-structure segmentation using Cardiac-SegNet.
Medical physics
Apr 1, 2021
PURPOSE: Cardiac boundary segmentation of echocardiographic images is important for cardiac function assessment and disease diagnosis. However, it is challenging to segment cardiac ventricles due to the low contrast-to-noise ratio and speckle noise o...
Edge-Sensitive Left Ventricle Segmentation Using Deep Reinforcement Learning.
Sensors (Basel, Switzerland)
Mar 29, 2021
Deep reinforcement learning (DRL) has been utilized in numerous computer vision tasks, such as object detection, autonomous driving, etc. However, relatively few DRL methods have been proposed in the area of image segmentation, particularly in left v...
Automated left and right ventricular chamber segmentation in cardiac magnetic resonance images using dense fully convolutional neural network.
Computer methods and programs in biomedicine
Mar 21, 2021
BACKGROUND AND OBJECTIVE: Segmentation of the left ventricular (LV) myocardium (Myo) and RV endocardium on cine cardiac magnetic resonance (CMR) images represents an essential step for cardiac-function evaluation and diagnosis. In order to have a com...
Validation of a deep-learning semantic segmentation approach to fully automate MRI-based left-ventricular deformation analysis in cardiotoxicity.
The British journal of radiology
Feb 24, 2021
OBJECTIVE: Left-ventricular (LV) strain measurements with the Displacement Encoding with Stimulated Echoes (DENSE) MRI sequence provide accurate estimates of cardiotoxicity damage related to chemotherapy for breast cancer. This study investigated an ...
A deep-learning semantic segmentation approach to fully automated MRI-based left-ventricular deformation analysis in cardiotoxicity.
Magnetic resonance imaging
Feb 8, 2021
Left-ventricular (LV) strain measurements with the Displacement Encoding with Stimulated Echoes (DENSE) MRI sequence provide accurate estimates of cardiotoxicity damage related to breast cancer chemotherapy. This study investigated an automated LV ch...
Artificial Intelligence-Powered Measurement of Left Ventricular Ejection Fraction Using a Handheld Ultrasound Device.
Ultrasound in medicine & biology
Jan 13, 2021
The aim of this study was to assess the accuracy of an algorithm for automated measurement of left ventricular ejection fraction (LVEF) available on handheld ultrasound devices (HUDs). One hundred twelve patients admitted to the cardiology department...
Automatic segmentation of ventricular volume by 3D ultrasonography in post haemorrhagic ventricular dilatation among preterm infants.
Scientific reports
Jan 12, 2021
To train, evaluate, and validate the application of a deep learning framework in three-dimensional ultrasound (3D US) for the automatic segmentation of ventricular volume in preterm infants with post haemorrhagic ventricular dilatation (PHVD). We tra...
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