AIMC Topic: Heart Ventricles
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A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images.
Computers in biology and medicine
Apr 24, 2023
Accurate segmentation of the left ventricle (LV) is crucial for evaluating myocardial perfusion SPECT (MPS) and assessing LV functions. In this study, a novel method combining deep learning with shape priors was developed and validated to extract the...
Left ventricle segmentation combining deep learning and deformable models with anatomical constraints.
Journal of biomedical informatics
Apr 21, 2023
Segmentation of the left ventricle is a key approach in Cardiac Magnetic Resonance Imaging for calculating biomarkers in diagnosis. Since there is substantial effort required from the expert, many automatic segmentation methods have been proposed, in...
A deep learning approach for fully automated cardiac shape modeling in tetralogy of Fallot.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Feb 27, 2023
BACKGROUND: Cardiac shape modeling is a useful computational tool that has provided quantitative insights into the mechanisms underlying dysfunction in heart disease. The manual input and time required to make cardiac shape models, however, limits th...
Image-based estimation of the left ventricular cavity volume using deep learning and Gaussian process with cardio-mechanical applications.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 24, 2023
In this investigation, an image-based method has been developed to estimate the volume of the left ventricular cavity using cardiac magnetic resonance (CMR) imaging data. Deep learning and Gaussian processes have been applied to bring the estimations...
EchoEFNet: Multi-task deep learning network for automatic calculation of left ventricular ejection fraction in 2D echocardiography.
Computers in biology and medicine
Feb 24, 2023
Left ventricular ejection fraction (LVEF) is essential for evaluating left ventricular systolic function. However, its clinical calculation requires the physician to interactively segment the left ventricle and obtain the mitral annulus and apical la...
Robot-Assisted Resection of Left Ventricular Papillary Fibroelastoma Arising From the Mitral Chordal Apparatus.
Innovations (Philadelphia, Pa.)
Feb 13, 2023
The application of robot-assisted thoracoscopy to cardiac surgery affords an opportunity to leverage the exceptional intraoperative exposure, visualization, and dexterity of the robotic platform. Here, we report the case of a 72-year-old woman who pr...
An Overview of Deep Learning Methods for Left Ventricle Segmentation.
Computational intelligence and neuroscience
Jan 30, 2023
Cardiac health diseases are one of the key causes of death around the globe. The number of heart patients has considerably increased during the pandemic. Therefore, it is crucial to assess and analyze the medical and cardiac images. Deep learning arc...
Cross-Domain Echocardiography Segmentation with Multi-Space Joint Adaptation.
Sensors (Basel, Switzerland)
Jan 28, 2023
The segmentation of the left ventricle endocardium (LV) and the left ventricle epicardium (LV) in echocardiography plays an important role in clinical diagnosis. Recently, deep neural networks have been the most commonly used approach for echocardiog...
A Tiny Matched Filter-Based CNN for Inter-Patient ECG Classification and Arrhythmia Detection at the Edge.
Sensors (Basel, Switzerland)
Jan 26, 2023
Automated electrocardiogram (ECG) classification using machine learning (ML) is extensively utilized for arrhythmia detection. Contemporary ML algorithms are typically deployed on the cloud, which may not always meet the availability and privacy requ...
Deep learning can yield clinically useful right ventricular segmentations faster than fully manual analysis.
Scientific reports
Jan 21, 2023
Right ventricular (RV) volumes are commonly obtained through time-consuming manual delineations of cardiac magnetic resonance (CMR) images. Deep learning-based methods can generate RV delineations, but few studies have assessed their ability to accel...
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