7 research outputs found
Neuromelanin-MRI using 2D GRE and deep learning: considerations for improving the visualization of substantia nigra and locus coeruleus
An optimized clinically feasible neuromelanin-MRI imaging protocol for
visualising the SN and LC simultaneously using deep learning reconstruction is
presented. We optimize flip-angle for optimal combined SN and LC depiction. We
also experimented with combinations of anisotropic and isotropic in-plane
resolution, partial vs full echoes and the number of averages. Phantom and
in-vivo experiments on three healthy volunteers illustrate that high-resolution
imaging combined with deep-learning denoising shows good depiction of the SN
and LC with a clinically feasible sequence of around 7 minutes.Comment: An article based on ECR and ISMRM abstracts, with more text & figure
Time-optimized Radio Frequency pulse design within hardware and sequence constraints for multiband MRI
Comprehensive brainstem imaging using MT, QSM and DTI for atypical parkinsonism diagnosis
Quantitative MRI protocol and decision model for a ‘one stop shop’ early-stage Parkinsonism diagnosis: Study design
Differentiating among early-stage parkinsonisms is a challenge in clinical practice. Quantitative MRI can aid the diagnostic process, but studies with singular MRI techniques have had limited success thus far. Our objective is to develop a multi-modal MRI method for this purpose. In this review we describe existing methods and present a dedicated quantitative MRI protocol, a decision model and a study design to validate our approach ahead of a pilot study. We present example imaging data from patients and a healthy control, which resemble related literature