AIMC Topic: Heart Ventricles
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Towards deep learning methods for quantification of the right ventricle using 2D echocardiography.
Future cardiology
Jun 10, 2024
Automatic Segmentation for Analysis of Murine Cardiac Ultrasound and Photoacoustic Image Data Using Deep Learning.
Ultrasound in medicine & biology
Jun 1, 2024
OBJECTIVE: Although there are methods to identify regions of interest (ROIs) from echocardiographic images of myocardial tissue, they are often time-consuming and difficult to create when image quality is poor. Further, while myocardial strain from u...
A novel multi-task machine learning classifier for rare disease patterning using cardiac strain imaging data.
Scientific reports
May 9, 2024
To provide accurate predictions, current machine learning-based solutions require large, manually labeled training datasets. We implement persistent homology (PH), a topological tool for studying the pattern of data, to analyze echocardiography-based...
CardSegNet: An adaptive hybrid CNN-vision transformer model for heart region segmentation in cardiac MRI.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Apr 16, 2024
Cardiovascular MRI (CMRI) is a non-invasive imaging technique adopted for assessing the blood circulatory system's structure and function. Precise image segmentation is required to measure cardiac parameters and diagnose abnormalities through CMRI da...
New era in right ventricular imaging with AI: Challenges and horizons.
International journal of cardiology
Apr 3, 2024
DeepMesh: Mesh-Based Cardiac Motion Tracking Using Deep Learning.
IEEE transactions on medical imaging
Apr 3, 2024
3D motion estimation from cine cardiac magnetic resonance (CMR) images is important for the assessment of cardiac function and the diagnosis of cardiovascular diseases. Current state-of-the art methods focus on estimating dense pixel-/voxel-wise moti...
A hybrid neural ordinary differential equation model of the cardiovascular system.
Journal of the Royal Society, Interface
Mar 20, 2024
In the human cardiovascular system (CVS), the interaction between the left and right ventricles of the heart is influenced by the septum and the pericardium. Computational models of the CVS can capture this interaction, but this often involves approx...
Machine learning approach using F-FDG-PET-radiomic features and the visibility of right ventricle F-FDG uptake for predicting clinical events in patients with cardiac sarcoidosis.
Japanese journal of radiology
Mar 16, 2024
OBJECTIVES: To investigate the usefulness of machine learning (ML) models using pretreatment F-FDG-PET-based radiomic features for predicting adverse clinical events (ACEs) in patients with cardiac sarcoidosis (CS).
Artificial intelligence: The future for multimodality imaging of right ventricle.
International journal of cardiology
Mar 14, 2024
The crucial pathophysiological and prognostic roles of the right ventricle in various diseases have been well-established. Nonetheless, conventional cardiovascular imaging modalities are frequently associated with intrinsic limitations when evaluatin...
Automated echocardiographic left ventricular dimension assessment in dogs using artificial intelligence: Development and validation.
Journal of veterinary internal medicine
Feb 16, 2024
BACKGROUND: Artificial intelligence (AI) could improve accuracy and reproducibility of echocardiographic measurements in dogs.
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