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Heart

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Evaluation of a delineation software for cardiac atlas-based autosegmentation: An example of the use of artificial intelligence in modern radiotherapy.

Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
PURPOSE: The primary objective of this work was to implement and evaluate a cardiac atlas-based autosegmentation technique based on the "Workflow Box" software (Mirada Medical, Oxford UK), in order to delineate cardiac substructures according to Euro...

Cardiac Segmentation With Strong Anatomical Guarantees.

IEEE transactions on medical imaging
Convolutional neural networks (CNN) have had unprecedented success in medical imaging and, in particular, in medical image segmentation. However, despite the fact that segmentation results are closer than ever to the inter-expert variability, CNNs ar...

Deep learning reconstruction for cardiac magnetic resonance fingerprinting T and T mapping.

Magnetic resonance in medicine
PURPOSE: To develop a deep learning method for rapidly reconstructing T and T maps from undersampled electrocardiogram (ECG) triggered cardiac magnetic resonance fingerprinting (cMRF) images.

Deep pyramid local attention neural network for cardiac structure segmentation in two-dimensional echocardiography.

Medical image analysis
Automatic semantic segmentation in 2D echocardiography is vital in clinical practice for assessing various cardiac functions and improving the diagnosis of cardiac diseases. However, two distinct problems have persisted in automatic segmentation in 2...

Classification of aortic stenosis using conventional machine learning and deep learning methods based on multi-dimensional cardio-mechanical signals.

Scientific reports
This paper introduces a study on the classification of aortic stenosis (AS) based on cardio-mechanical signals collected using non-invasive wearable inertial sensors. Measurements were taken from 21 AS patients and 13 non-AS subjects. A feature analy...

Steps to use artificial intelligence in echocardiography.

Journal of echocardiography
Artificial intelligence (AI) has influenced every field of cardiovascular imaging in all phases from acquisition to reporting. Compared with computed tomography and magnetic resonance imaging, there is an issue of high observer variation in the inter...

Deep learning-based reduced order models in cardiac electrophysiology.

PloS one
Predicting the electrical behavior of the heart, from the cellular scale to the tissue level, relies on the numerical approximation of coupled nonlinear dynamical systems. These systems describe the cardiac action potential, that is the polarization/...

Artificial intelligence in cardiac radiology.

La Radiologia medica
Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementation will be focused on the automatization tasks, improving diagnostic accuracy and reducing reading time. Many studies investigate the potential role ...

Noninvasive estimation of aortic hemodynamics and cardiac contractility using machine learning.

Scientific reports
Cardiac and aortic characteristics are crucial for cardiovascular disease detection. However, noninvasive estimation of aortic hemodynamics and cardiac contractility is still challenging. This paper investigated the potential of estimating aortic sys...

Cardiac magnetic resonance image segmentation based on convolutional neural network.

Computer methods and programs in biomedicine
OBJECTIVE: In cardiac medical imaging, the extraction and segmentation of the part of interest is the key to the diagnosis of heart disease. Due to irregular diastole and contraction, magnetic resonance imaging (MRI) images have poorly defined bounda...