AIMC Topic: Heart Ventricles

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Utilizing Artificial Intelligence-Based Deformable Registration for Global and Layer-Specific Cardiac MRI Strain Analysis in Healthy Children and Young Adults.

Academic radiology
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)
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
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
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
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
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 ...

Robot-Assisted Excision of a Left Ventricular Myxoma and Hemangioma.

Innovations (Philadelphia, Pa.)
Left ventricular masses are rare entities that often require surgical excision when diagnosed due to the risk of embolization. We report 2 separate patients presenting with evidence of cerebral embolization both of whom were diagnosed with isolated l...

Comparison of post reconstruction- and reconstruction-based deep learning denoising methods in cardiac SPECT.

Biomedical physics & engineering express
. The quality of myocardial perfusion SPECT (MPS) images is often hampered by low count statistics. Poor image quality might hinder reporting the studies and in the worst case lead to erroneous diagnosis. Deep learning (DL)-based methods can be used ...

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...