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Heart Ventricles

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Development of a Visualization Deep Learning Model for Classifying Origins of Ventricular Arrhythmias.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: Several algorithms have been proposed for differentiating the right and left outflow tracts (RVOT/LVOT) arrhythmia origins from 12-lead electrocardiograms (ECGs); however, the procedure is complicated. A deep learning (DL) model, a form o...

Training and clinical testing of artificial intelligence derived right atrial cardiovascular magnetic resonance measurements.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Right atrial (RA) area predicts mortality in patients with pulmonary hypertension, and is recommended by the European Society of Cardiology/European Respiratory Society pulmonary hypertension guidelines. The advent of deep learning may al...

The auto segmentation for cardiac structures using a dual-input deep learning network based on vision saliency and transformer.

Journal of applied clinical medical physics
PURPOSE: Accurate segmentation of cardiac structures on coronary CT angiography (CCTA) images is crucial for the morphological analysis, measurement, and functional evaluation. In this study, we achieve accurate automatic segmentation of cardiac stru...

A U-snake based deep learning network for right ventricle segmentation.

Medical physics
PURPOSE: Ventricular segmentation is of great importance for the heart condition monitoring. However, manual segmentation is time-consuming, cumbersome, and subjective. Many segmentation methods perform poorly due to the complex structure and uncerta...

MCAL: An Anatomical Knowledge Learning Model for Myocardial Segmentation in 2-D Echocardiography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Segmentation of the left ventricular (LV) myocardium in 2-D echocardiography is essential for clinical decision making, especially in geometry measurement and index computation. However, segmenting the myocardium is a time-consuming process and chall...

Automatic Cardiac Structure Contouring for Small Datasets with Cascaded Deep Learning Models.

Journal of medical systems
Cardiac structure contouring is a time consuming and tedious manual activity used for radiotherapeutic dose toxicity planning. We developed an automatic cardiac structure segmentation pipeline for use in low-dose non-contrast planning CT based on dee...

An Improved 3D Deep Learning-Based Segmentation of Left Ventricular Myocardial Diseases from Delayed-Enhancement MRI with Inclusion and Classification Prior Information U-Net (ICPIU-Net).

Sensors (Basel, Switzerland)
Accurate segmentation of the myocardial scar may supply relevant advancements in predicting and controlling deadly ventricular arrhythmias in subjects with cardiovascular disease. In this paper, we propose the architecture of inclusion and classifica...

Fully automated intracardiac 4D flow MRI post-processing using deep learning for biventricular segmentation.

European radiology
OBJECTIVES: 4D flow MRI allows for a comprehensive assessment of intracardiac blood flow, useful for assessing cardiovascular diseases, but post-processing requires time-consuming ventricular segmentation throughout the cardiac cycle and is prone to ...

Improving robustness of automatic cardiac function quantification from cine magnetic resonance imaging using synthetic image data.

Scientific reports
Although having been the subject of intense research over the years, cardiac function quantification from MRI is still not a fully automatic process in the clinical practice. This is partly due to the shortage of training data covering all relevant c...

Machine Learning-Based Prediction of Myocardial Recovery in Patients With Left Ventricular Assist Device Support.

Circulation. Heart failure
BACKGROUND: Prospective studies demonstrate that aggressive pharmacological therapy combined with pump speed optimization may result in myocardial recovery in larger numbers of patients supported with left ventricular assist device (LVAD). This study...