bioRxiv (Cold Spring Harbor Laboratory) · 2020 · 10 citations · 83 references
MedicineBioengineeringRadiologyBiomedical ImagingDiagnostic ImagingDiagnostic RadiologyImage ReconstructionMagnetic Resonance Image ReconstructionMagnetic Resonance ImagingMagnetic Resonance Imaging PhysicsMedical ImagingMedical Imaging PhysicsMultiparametric ImagingMultiparametric Magnetic Resonance Imaging (Mri)Quantitative Susceptibility Mapping
Abstract Purpose To create a realistic in-silico head phantom for the second Quantitative Susceptibility Mapping (QSM) Reconstruction Challenge and for future evaluations of processing algorithms for QSM. Methods We created a digital whole-head tissue property phantom by segmenting and post-processing high-resolution (0.64mm isotropic), multi-parametric MRI data acquired at 7T from a healthy volunteer. We simulated the steady-state magnetization at 7T using a Bloch simulator and mimicked a Cartesian sampling scheme through Fourier-based processing. Computer code for generating the phantom and performing the MR simulation was designed to facilitate flexible modifications of the phantom in the future, such as the inclusion of pathologies, as well as the simulation of a wide range of acquisition protocols. Specifically, the following parameters and effects were implemented: repetition time and echo time, voxel size, background fields, and RF phase biases. Diffusion weighted imaging phantom data is provided allowing future investigations of tissue microstructure effects in phase and QSM algorithms. Results The brain-part of the phantom featured realistic morphology with spatial variations in relaxation and susceptibility values similar to the in vivo setting. We demonstrated some of the phantom’s properties, including the possibility of generating phase data with non-linear evolution over echo time due to partial volume effects or complex distributions of frequency shifts within the voxel. Conclusion The presented phantom and computer programs are publicly available and may serve as a ground truth in future assessments of the faithfulness of quantitative susceptibility reconstruction algorithms.
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SENSE: Sensitivity encoding for fast MRI
Klaas P. Pruessmann, Markus Weiger, Markus B. Scheidegger et al. · Magnetic Resonance in Medicine · 1999 · 6.1K citations
THE EFFECT OF AGE ON THE NON‐HAEMIN IRON IN THE HUMAN BRAIN
Bo Hallgren, Patrick Sourander · Journal of Neurochemistry · 1958 · 1.4K citations
Medicine, Neurobiology, Neuroscience +10