AIMC Topic: Gadolinium
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Automated assessment of cardiac pathologies on cardiac MRI using T1-mapping and late gadolinium phase sensitive inversion recovery sequences with deep learning.
BMC medical imaging
Feb 13, 2024
BACKGROUND: A deep learning (DL) model that automatically detects cardiac pathologies on cardiac MRI may help streamline the diagnostic workflow. To develop a DL model to detect cardiac pathologies on cardiac MRI T1-mapping and late gadolinium phase ...
Automated inversion time selection for late gadolinium-enhanced cardiac magnetic resonance imaging.
European radiology
Feb 10, 2024
OBJECTIVES: To develop and share a deep learning method that can accurately identify optimal inversion time (TI) from multi-vendor, multi-institutional and multi-field strength inversion scout (TI scout) sequences for late gadolinium enhancement card...
Compressed sensing with deep learning reconstruction: Improving capability of gadolinium-EOB-enhanced 3D T1WI.
Magnetic resonance imaging
Feb 1, 2024
PURPOSE: The purpose of this study was to determine the utility of compressed sensing (CS) with deep learning reconstruction (DLR) for improving spatial resolution, image quality and focal liver lesion detection on high-resolution contrast-enhanced T...
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.
Reducing Gadolinium Contrast With Artificial Intelligence.
Journal of magnetic resonance imaging : JMRI
Oct 31, 2023
Gadolinium contrast is an important agent in magnetic resonance imaging (MRI), particularly in neuroimaging where it can help identify blood-brain barrier breakdown from an inflammatory, infectious, or neoplastic process. However, gadolinium contrast...
Evaluation of late gadolinium enhancement cardiac MRI using deep learning reconstruction.
Acta radiologica (Stockholm, Sweden : 1987)
Sep 12, 2023
BACKGROUND: Deep learning (DL)-based methods have been used to improve the imaging quality of magnetic resonance imaging (MRI) by denoising.
Amplifying the Effects of Contrast Agents on Magnetic Resonance Images Using a Deep Learning Method Trained on Synthetic Data.
Investigative radiology
Jul 28, 2023
OBJECTIVES: Artificial intelligence (AI) methods can be applied to enhance contrast in diagnostic images beyond that attainable with the standard doses of contrast agents (CAs) normally used in the clinic, thus potentially increasing diagnostic power...
Artificial Contrast: Deep Learning for Reducing Gadolinium-Based Contrast Agents in Neuroradiology.
Investigative radiology
Feb 22, 2023
Deep learning approaches are playing an ever-increasing role throughout diagnostic medicine, especially in neuroradiology, to solve a wide range of problems such as segmentation, synthesis of missing sequences, and image quality improvement. Of parti...
Optimization of null point in Look-Locker images for myocardial late gadolinium enhancement imaging using deep learning and a smartphone.
European radiology
Feb 21, 2023
OBJECTIVES: To determine the optimal inversion time (TI) from Look-Locker scout images using a convolutional neural network (CNN) and to investigate the feasibility of correcting TI using a smartphone.
An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar.
Computer methods and programs in biomedicine
Dec 20, 2022
BACKGROUND AND OBJECTIVES: Myocardial infarction scar (MIS) assessment by cardiac magnetic resonance provides prognostic information and guides patients' clinical management. However, MIS segmentation is time-consuming and not performed routinely. Th...
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