AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Heart

Showing 421 to 430 of 453 articles

Clear Filters

Autosegmentation of lung computed tomography datasets using deep learning U-Net architecture.

Journal of cancer research and therapeutics
AIM: Current radiotherapy treatment techniques require a large amount of imaging data for treatment planning which demand significant clinician's time to segment target volume and organs at risk (OARs). In this study, we propose to use U-net-based ar...

Automated Measurement of Native T1 and Extracellular Volume Fraction in Cardiac Magnetic Resonance Imaging Using a Commercially Available Deep Learning Algorithm.

Korean journal of radiology
OBJECTIVE: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extrace...

Segmentation of human aorta using 3D nnU-net-oriented deep learning.

The Review of scientific instruments
Computed tomography angiography (CTA) has become the main imaging technique for cardiovascular diseases. Before performing the transcatheter aortic valve intervention operation, segmenting images of the aortic sinus and nearby cardiovascular tissue f...

Denoising using deep-learning-based reconstruction for whole-heart coronary MRA with sub-millimeter isotropic resolution at 3 T: a volunteer study.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE The aim of this study was to assess the usefulness of denoising deep-learning-based reconstruction (dDLR) to improve image quality and vessel delineation in noncontrast 3-T wholeheart coronary magnetic resonance angiography (WHCMRA) with sub-...

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...