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Gadolinium

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Automatic segmentation of gadolinium-enhancing lesions in multiple sclerosis using deep learning from clinical MRI.

PloS one
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...

A generic deep learning model for reduced gadolinium dose in contrast-enhanced brain MRI.

Magnetic resonance in medicine
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...

Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy.

Circulation
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...

[Early Assessment of Myocardial Fibrosis of Hypertrophic Cardiomyopathy with Native-T1-Mapping-Based Deep Learning: A Preliminary Study].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: To explore the diagnostic performance of deep learning (DL) model in early detection of the interstitial myocardial fibrosis using native T1 maps of hypertrophic cardiomyopathy (HCM) without late gadolinium enhancement (LGE).

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
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...

Adaptive Hierarchical Dual Consistency for Semi-Supervised Left Atrium Segmentation on Cross-Domain Data.

IEEE transactions on medical imaging
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...

Can Deep Learning Replace Gadolinium in Neuro-Oncology?: A Reader Study.

Investigative radiology
MATERIALS AND METHODS: This monocentric retrospective study leveraged 200 multiparametric brain MRIs acquired between November 2019 and February 2020 at Gustave Roussy Cancer Campus (Villejuif, France). A total of 145 patients were included: 107 form...