AIMC Topic: Heart

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Evaluation of an artificial intelligence-based system for echocardiographic estimation of right atrial pressure.

The international journal of cardiovascular imaging
Current noninvasive estimation of right atrial pressure (RAP) by inferior vena cava (IVC) measurement during echocardiography may have significant inter-rater variability due to different levels of observers' experience. Therefore, there is a need to...

Artificial intelligence in cardiac computed tomography.

Progress in cardiovascular diseases
Artificial Intelligence (AI) is a broad discipline of computer science and engineering. Modern application of AI encompasses intelligent models and algorithms for automated data analysis and processing, data generation, and prediction with applicatio...

Clinical perspectives on the adoption of the artificial intelligence-enabled electrocardiogram.

Journal of electrocardiology
The 12‑lead electrocardiogram (ECG) is a common and inexpensive diagnostic modality available at scale. The ECG reflects electrical activity throughout the cardiac cycle and is increasingly recognized to contain rich signal relevant across the spectr...

Comparison of manual and artificial intelligence based quantification of myocardial strain by feature tracking-a cardiovascular MR study in health and disease.

European radiology
OBJECTIVES: The analysis of myocardial deformation using feature tracking in cardiovascular MR allows for the assessment of global and segmental strain values. The aim of this study was to compare strain values derived from artificial intelligence (A...

Optimizing Deep Learning for Cardiac MRI Segmentation: The Impact of Automated Slice Range Classification.

Academic radiology
RATIONALE AND OBJECTIVES: Cardiac magnetic resonance imaging is crucial for diagnosing cardiovascular diseases, but lengthy postprocessing and manual segmentation can lead to observer bias. Deep learning (DL) has been proposed for automated cardiac s...

Siamese pyramidal deep learning network for strain estimation in 3D cardiac cine-MR.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Strain represents the quantification of regional tissue deformation within a given area. Myocardial strain has demonstrated considerable utility as an indicator for the assessment of cardiac function. Notably, it exhibits greater sensitivity in detec...

Respiratory signal estimation for cardiac perfusion SPECT using deep learning.

Medical physics
BACKGROUND: Respiratory motion induces artifacts in reconstructed cardiac perfusion SPECT images. Correction for respiratory motion often relies on a respiratory signal describing the heart displacements during breathing. However, using external trac...

BayeSeg: Bayesian modeling for medical image segmentation with interpretable generalizability.

Medical image analysis
Due to the cross-domain distribution shift aroused from diverse medical imaging systems, many deep learning segmentation methods fail to perform well on unseen data, which limits their real-world applicability. Recent works have shown the benefits of...

SequenceMorph: A Unified Unsupervised Learning Framework for Motion Tracking on Cardiac Image Sequences.

IEEE transactions on pattern analysis and machine intelligence
Modern medical imaging techniques, such as ultrasound (US) and cardiac magnetic resonance (MR) imaging, have enabled the evaluation of myocardial deformation directly from an image sequence. While many traditional cardiac motion tracking methods have...