AIMC Topic: Heart Ventricles
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Assessment of deep learning segmentation for real-time free-breathing cardiac magnetic resonance imaging at rest and under exercise stress.
Scientific reports
Feb 14, 2024
In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been developed and analyzed. However, nearly all of them are focused on cine CMR under breathold. In this work, accuracy of deep learning methods is assessed...
Strong Diagnostic Performance of Single Energy 256-row Multidetector Computed Tomography with Deep Learning Image Reconstruction in the Assessment of Myocardial Fibrosis.
Internal medicine (Tokyo, Japan)
Feb 12, 2024
Objective Although magnetic resonance imaging (MRI) is the gold standard for evaluating abnormal myocardial fibrosis and extracellular volume (ECV) of the left ventricular myocardium (LVM), a similar evaluation has recently become possible using comp...
Engineers use a porcine heart scaffold to create a bio-robotic model of the right ventricle.
Artificial organs
Jan 12, 2024
The simulator can provide a dynamic and sophisticated platform to further aid in the study of the right heart in an era where numerous technologies are rapidly emerging in this space.
Deep learning based automated left ventricle segmentation and flow quantification in 4D flow cardiac MRI.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Jan 10, 2024
BACKGROUND: 4D flow MRI enables assessment of cardiac function and intra-cardiac blood flow dynamics from a single acquisition. However, due to the poor contrast between the chambers and surrounding tissue, quantitative analysis relies on the segment...
Coronary Circulation
Myocardial Perfusion Imaging
Magnetic Resonance Imaging, Cine
Image Interpretation, Computer-Assisted
Automation
Blood Flow Velocity
Deep Learning
Predictive Value of Tests
Heart Ventricles
Databases, Factual
Female
Reproducibility of Results
Male
Ventricular Function, Left
Middle Aged
Humans
Utilizing Artificial Intelligence-Based Deformable Registration for Global and Layer-Specific Cardiac MRI Strain Analysis in Healthy Children and Young Adults.
Academic radiology
Jan 4, 2024
RATIONALE AND OBJECTIVES: The absence of published reference values for multilayer-specific strain measurement using cardiac magnetic resonance (CMR) in young healthy individuals limits its use. This study aimed to establish normal global and layer-s...
Deep learning for classification of late gadolinium enhancement lesions based on the 16-segment left ventricular model.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Dec 5, 2023
PURPOSE: This study aimed to develop and validate a deep learning-based method that allows for segmental analysis of myocardial late gadolinium enhancement (LGE) lesions.
Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation.
International journal for numerical methods in biomedical engineering
Nov 3, 2023
Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such...
Deep learning assisted measurement of echocardiographic left heart parameters: improvement in interobserver variability and workflow efficiency.
The international journal of cardiovascular imaging
Oct 23, 2023
Machine learning techniques designed to recognize views and perform measurements are increasingly used to address the need for automation of the interpretation of echocardiographic images. The current study was designed to determine whether a recentl...
Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution.
Diagnostic and interventional imaging
Oct 11, 2023
PURPOSE: The purpose of this study was to propose a deep learning-based approach to detect pulmonary embolism and quantify its severity using the Qanadli score and the right-to-left ventricle diameter (RV/LV) ratio on three-dimensional (3D) computed ...
HDL: Hybrid Deep Learning for the Synthesis of Myocardial Velocity Maps in Digital Twins for Cardiac Analysis.
IEEE journal of biomedical and health informatics
Oct 5, 2023
Synthetic digital twins based on medical data accelerate the acquisition, labelling and decision making procedure in digital healthcare. A core part of digital healthcare twins is model-based data synthesis, which permits the generation of realistic ...
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