AIMC Topic: Gadolinium
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An Improved 3D Deep Learning-Based Segmentation of Left Ventricular Myocardial Diseases from Delayed-Enhancement MRI with Inclusion and Classification Prior Information U-Net (ICPIU-Net).
Sensors (Basel, Switzerland)
Mar 8, 2022
Accurate segmentation of the myocardial scar may supply relevant advancements in predicting and controlling deadly ventricular arrhythmias in subjects with cardiovascular disease. In this paper, we propose the architecture of inclusion and classifica...
Predicting adverse cardiac events in sarcoidosis: deep learning from automated characterization of regional myocardial remodeling.
The international journal of cardiovascular imaging
Feb 22, 2022
Recognizing early cardiac sarcoidosis (CS) imaging phenotypes can help identify opportunities for effective treatment before irreversible myocardial pathology occurs. We aimed to characterize regional CS myocardial remodeling features correlating wit...
Adaptive Hierarchical Dual Consistency for Semi-Supervised Left Atrium Segmentation on Cross-Domain Data.
IEEE transactions on medical imaging
Feb 2, 2022
Semi-supervised learning provides great significance in left atrium (LA) segmentation model learning with insufficient labelled data. Generalising semi-supervised learning to cross-domain data is of high importance to further improve model robustness...
Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study.
The Lancet. Digital health
Oct 20, 2021
BACKGROUND: Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after r...
Contrast Media
Magnetic Resonance Imaging
Glioblastoma
Neoplasms
Disease Progression
Deep Learning
Germany
Gadolinium
Diffusion Magnetic Resonance Imaging
Radiology
Feasibility Studies
Tumor Burden
Algorithms
Brain
Prognosis
Retrospective Studies
Brain Neoplasms
Middle Aged
Humans
Neural Networks, Computer
Feasibility of late gadolinium enhancement (LGE) in ischemic cardiomyopathy using 2D-multisegment LGE combined with artificial intelligence reconstruction deep learning noise reduction algorithm.
International journal of cardiology
Sep 10, 2021
BACKGROUND: Despite the low spatial resolution of 2D-multisegment late gadolinium enhancement (2D-MSLGE) sequences, it may be useful in uncooperative patients instead of standard 2D single segmented inversion recovery gradient echo late gadolinium en...
Automatic segmentation of gadolinium-enhancing lesions in multiple sclerosis using deep learning from clinical MRI.
PloS one
Sep 1, 2021
Gadolinium-enhancing lesions reflect active disease and are critical for in-patient monitoring in multiple sclerosis (MS). In this work, we have developed the first fully automated method to segment and count the gadolinium-enhancing lesions from rou...
Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy.
Circulation
Jul 7, 2021
BACKGROUND: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for noninvasive myocardial tissue characterization but requires intravenous contrast agent administration. It is highly desired to deve...
A generic deep learning model for reduced gadolinium dose in contrast-enhanced brain MRI.
Magnetic resonance in medicine
Apr 29, 2021
PURPOSE: With rising safety concerns over the use of gadolinium-based contrast agents (GBCAs) in contrast-enhanced MRI, there is a need for dose reduction while maintaining diagnostic capability. This work proposes comprehensive technical solutions f...
Editorial for "Improved Quantification of Myocardium Scar in Late Gadolinium Enhancement Images: Deep Learning Based Image Fusion Approach".
Journal of magnetic resonance imaging : JMRI
Mar 29, 2021
Editorial For "Reduction of Contrast Agent Dose in Cardiovascular MR Angiography Using Deep Learning".
Journal of magnetic resonance imaging : JMRI
Mar 26, 2021
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