AIMC Topic: Heart

Clear Filters Showing 471 to 480 of 499 articles

TF-Unet:An automatic cardiac MRI image segmentation method.

Mathematical biosciences and engineering : MBE
Personalized heart models are widely used to study the mechanisms of cardiac arrhythmias and have been used to guide clinical ablation of different types of arrhythmias in recent years. MRI images are now mostly used for model building. In cardiac mo...

Localization of Point-of-Interest Positions on Cardiac Surface for Robotic-Assisted Beating Heart Surgery.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
One of the critical components of robotic-assisted beating heart surgery is precise localization of a point-of-interest (POI) position on cardiac surface, which needs to be tracked by the robotic instruments. This is challenging as the incoming senso...

Deep Learning-Based Segmentation and Uncertainty Assessment for Automated Analysis of Myocardial Perfusion MRI Datasets Using Patch-Level Training and Advanced Data Augmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this work, we develop a patch-level training approach and a task-driven intensity-based augmentation method for deep-learning-based segmentation of motion-corrected perfusion cardiac magnetic resonance imaging (MRI) datasets. Further, the proposed...

More than meets the eye: Using AI to identify reduced heart function by electrocardiograms.

Med (New York, N.Y.)
Electrocardiographic (ECG) assessment of patients with suspected heart disease is a bedrock of cardiology for diagnosing conduction system disease, arrhythmias, and heart attack. Now, using AI-assisted interpretation of ECGs, the signals within these...

The current state of artificial intelligence in cardiac transplantation.

Current opinion in organ transplantation
PURPOSE OF REVIEW: The field of heart transplantation is a complex practice that combines both science and art to optimize the quality and quantity of an organ transplant recipient's life span. In the current age of Transplant Medicine there are many...

Semantic Anomaly Detection in Medical Time Series.

Studies in health technology and informatics
The main goal of this project was to define and evaluate a new unsupervised deep learning approach that can differentiate between normal and anomalous intervals of signals like the electrical activity of the heart (ECG). Denoising autoencoders based ...

Potential Role of Artificial Intelligence in Cardiac Magnetic Resonance Imaging: Can It Help Clinicians in Making a Diagnosis?

Journal of thoracic imaging
In the era of modern medicine, artificial intelligence (AI) is a growing field of interest which is experiencing a steady development. Several applications of AI have been applied to various aspects of cardiac magnetic resonance to assist clinicians ...

Deep learning formulation of electrocardiographic imaging integrating image and signal information with data-driven regularization.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
AIMS: Electrocardiographic imaging (ECGI) is a promising tool to map the electrical activity of the heart non-invasively using body surface potentials (BSP). However, it is still challenging due to the mathematically ill-posed nature of the inverse p...