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Register a new userImproving MRIs slice selectivity in the presence of strong, metal-derived inhomogeneities
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Purpose: To develop schemes that deliver faithful 2D slices near field heterogeneities of the kind arising from non-ferromagnetic metal implants, with reduced artifacts and shorter scan times. Methods: An excitation scheme relying on cross-term spatio-temporal encoding (xSPEN) was used as basis for developing the new inhomogeneity-insensitive, slice-selective pulse scheme. The resulting Fully refOCUSED cross-term SPatiotemporal ENcoding (FOCUSED-xSPEN) approach involved four adiabatic sweeps. The method was evaluated in silico, in vitro and in vivo using mice models, and compared against a number of existing and of novel alternatives based on both conventional and swept RF pulses, including an analogous method based on LASERs selectivity spatial selectivity. Results: Calculations and experiments confirmed that multi-sweep derivatives of xSPEN and LASER can deliver localized excitation profiles, centered at the intended positions and endowed with enhanced immunity to B0 and B1 distortions. This, however, is achieved at the expense of higher SAR than non-swept counterparts. Furthermore, single-shot FOCUSED-xSPEN and LASER profiles covered limited off-resonance ranges. This could be extended to bands covering arbitrary off-resonance values with uniform slice widths, by looping the experiments over a number of scans possessing suitable transmission and reception offsets. Conclusions: A series of novel approaches were introduced to select slices near metals, delivering robustness against Bo and B1+ field inhomogeneities.
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The size of micromagnetic structures, such as domain walls or vortices, is comparable to the exchange length of the ferromagnet. Both, the exchange length of the stray field $l_s$ and the magnetocrystalline exchange length $l_k$ are material-dependent quantities that usually lie in the nanometer range. This emphasizes the theoretical challenges associated with the mesoscopic nature of micromagnetism: the magnetic structures are much larger than the atomic lattice constant, but at the same time much smaller than the sample size. In computer simulations, the smallest exchange length serves as an estimate for the largest cell size admissible to prevent appreciable discretization errors. This general rule is not valid in special situations where the magnetization becomes particularly inhomogeneous. When such strongly inhomogeneous structures develop, micromagnetic simulations inevitably contain systematic and numerical errors. It is suggested to combine micromagnetic theory with a Heisenberg model to resolve such problems. We analyze cases where strongly inhomogeneous structures pose limits to standard micromagnetic simulations, arising from fundamental aspects as well as from numerical drawbacks.
Neurodegenerative diseases are frequently associated with structural changes in the brain. Magnetic Resonance Imaging (MRI) scans can show these variations and therefore be used as a supportive feature for a number of neurodegenerative diseases. The hippocampus has been known to be a biomarker for Alzheimer disease and other neurological and psychiatric diseases. However, it requires accurate, robust and reproducible delineation of hippocampal structures. Fully automatic methods are usually the voxel based approach, for each voxel a number of local features were calculated. In this paper we compared four different techniques for feature selection from a set of 315 features extracted for each voxel: (i) filter method based on the Kolmogorov-Smirnov test; two wrapper methods, respectively, (ii) Sequential Forward Selection and (iii) Sequential Backward Elimination; and (iv) embedded method based on the Random Forest Classifier on a set of 10 T1-weighted brain MRIs and tested on an independent set of 25 subjects. The resulting segmentations were compared with manual reference labelling. By using only 23 features for each voxel (sequential backward elimination) we obtained comparable state of-the-art performances with respect to the standard tool FreeSurfer.
We investigate the 5d transition metal oxide BaOsO$_3$ within a combination of density functional theory (DFT) and dynamical mean-field theory (DMFT), using a matrix-product-state impurity solver. BaOsO$_3$ has 4 electrons in the t$_{2g}$ shell akin to ruthenates but stronger spin-orbit coupling (SOC) and is thus expected to reveal an interplay of Hunds metal behavior with SOC. We explore the paramagnetic phase diagram as a function of SOC and Hubbard interaction strengths, identifying metallic, band (van-Vleck) insulating and Mott insulating regions. At the physical values of the two couplings we find that BaOsO$_3$ is still situated inside the metallic region and has a moderate quasiparticle renormalization $m^*/m approx 2$; consistent with specific heat measurements. SOC plays an important role in suppressing electronic correlations (found in the vanishing SOC case) through the splitting of a van-Hove singularity (vHs) close to the Fermi energy, but is insufficient to push the material into an insulating van-Vleck regime. In spite of the strong effect of SOC, BaOsO$_3$ can be best pictured as a moderately correlated Hunds metal.
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