Generalised Super Resolution for Quantitative MRI Using Self-supervised Mixture of Experts

Multi-modal and multi-contrast imaging datasets have diverse voxel-wise intensities. For example, quantitative MRI acquisition protocols are designed specifically to yield multiple images with widely-varying contrast that inform models relating MR signals to tissue characteristics. The large variance across images in such data prevents the use of standard normalisation techniques, making super resolution highly challenging. We propose a novel self-supervised mixture-of-experts (SS-MoE) paradigm for deep neural networks, and hence present a method enabling improved super resolution of data where image intensities are diverse and have large variance. Unlike the conventional MoE that automatically aggregates expert results for each input, we explicitly assign an input to the corresponding expert based on the predictive pseudo error labels in a self-supervised fashion. A new gater module is trained to discriminate the error levels of inputs estimated by Multiscale Quantile Segmentation. We show that our new paradigm reduces the error and improves the robustness when super resolving combined diffusion-relaxometry MRI data from the Super MUDI dataset. Our approach is suitable for a wide range of quantitative MRI techniques, and multi-contrast or multi-modal imaging techniques in general. It could be applied to super resolve images with inadequate resolution, or reduce the scanning time needed to acquire images of the required resolution. The source code and the trained models are available at https://github.com/hongxiangharry/SS-MoE

Synchrotron Mössbauer spectroscopic study of ferropericlase at high pressures and temperatures

The electronic spin state of Fe^(2+) in ferropericlase, (Mg_(0.75)Fe_(0.25))O, transitions from a high-spin (spin unpaired) to low-spin (spin paired) state within the Earth’s mid-lower mantle region. To better understand the local electronic environment of high-spin Fe^(2+) ions in ferropericlase near the transition, we obtained synchrotron Mössbauer spectra (SMS) of (Mg_(0.75),Fe_(0.25))O in externally heated and laser-heated diamond anvil cells at relevant high pressures and temperatures. Results show that the quadrupole splitting (QS) of the dominant high-spin Fe^(2+) site decreases with increasing temperature at static high pressure. The QS values at constant pressure are fitted to a temperature-dependent Boltzmann distribution model, which permits estimation of the crystal-field splitting energy (Δ_3) between the d_(xy_ and d_(xz) or d_(zy) orbitals of the t_(2g) states in a distorted octahedral Fe^(2+) site. The derived Δ_3 increases from approximately 36 meV at 1 GPa to 95 meV at 40 GPa, revealing that both high pressure and high temperature have significant effects on the 3d electronic shells of Fe^(2+) in ferropericlase. The SMS spectra collected from the laser-heated diamond cells within the time window of 146 ns also indicate that QS significantly decreases at very high temperatures. A larger splitting of the energy levels at high temperatures and pressures should broaden the spin crossover in ferropericlase because the degeneracy of energy levels is partially lifted. Our results provide information on the hyperfine parameters and crystal-field splitting energy of high-spin Fe^(2+) in ferropericlase at high pressures and temperatures, relevant to the electronic structure of iron in oxides in the deep lower mantle

Learning to Address Intra-segment Misclassification in Retinal Imaging

Accurate multi-class segmentation is a long-standing challenge in medical imaging, especially in scenarios where classes share strong similarity. Segmenting retinal blood vessels in retinal photographs is one such scenario, in which arteries and veins need to be identified and differentiated from each other and from the background. Intra-segment misclassification, i.e. veins classified as arteries or vice versa, frequently occurs when arteries and veins intersect, whereas in binary retinal vessel segmentation, error rates are much lower. We thus propose a new approach that decomposes multi-class segmentation into multiple binary, followed by a binary-to-multi-class fusion network. The network merges representations of artery, vein, and multi-class feature maps, each of which are supervised by expert vessel annotation in adversarial training. A skip-connection based merging process explicitly maintains class-specific gradients to avoid gradient vanishing in deep layers, to favor the discriminative features. The results show that, our model respectively improves F1-score by 4.4%, 5.1%, and 4.2% compared with three state-of-the-art deep learning based methods on DRIVE-AV, LES-AV, and HRF-AV data sets. Code: https://github.com/rmaphoh/Learning-AVSegmentatio

Learning to Address Intra-segment Misclassification in Retinal Imaging

Accurate multi-class segmentation is a long-standing challenge in medical imaging, especially in scenarios where classes share strong similarity. Segmenting retinal blood vessels in retinal photographs is one such scenario, in which arteries and veins need to be identified and differentiated from each other and from the background. Intra-segment misclassification, i.e. veins classified as arteries or vice versa, frequently occurs when arteries and veins intersect, whereas in binary retinal vessel segmentation, error rates are much lower. We thus propose a new approach that decomposes multi-class segmentation into multiple binary, followed by a binary-to-multi-class fusion network. The network merges representations of artery, vein, and multi-class feature maps, each of which are supervised by expert vessel annotation in adversarial training. A skip-connection based merging process explicitly maintains class-specific gradients to avoid gradient vanishing in deep layers, to favor the discriminative features. The results show that, our model respectively improves F1-score by 4.4%, 5.1%, and 4.2% compared with three state-of-the-art deep learning based methods on DRIVE-AV, LES-AV, and HRF-AV data sets. Code: https://github.com/rmaphoh/Learning-AVSegmentatio

Association Among Serum Perfluoroalkyl Chemicals, Glucose Homeostasis, and Metabolic Syndrome in Adolescents and Adults

OBJECTIVE - Perfluoroalkyl chemicals (PFCs) have been used worldwide in a variety of consumer products. The effect of PFCs on glucose homeostasis is not known. RESEARCH DESIGN AND METHODS - We examined 474 adolescents and 969 adults with reliable serum measures of metabolic syndrome profile from the National Health and Nutrition Examination Survey 1999-2000 and 2003-2004. RESULTS - In adolescents, increased serum perfluorononanoic acid (PFNA) concentrations were associated with hyperglycemia (odds ratio [OR] 3.16 [95% Cl 1.39-7.16], P < 0.05). Increased serum PFNA concentrations also have favorable associations with serum HDL cholesterol (0.67 [0.45-0.99], P < 0.05). Overall, increased serum PFNA concentrations were inversely correlated with the prevalence of the metabolic syndrome (0.37 [0.21-0.64], P < 0.005). In adults, increased serum perfluorooctanoic acid concentrations were significantly associated with increased beta-cell function (beta coefficient 0.07 +/- 0.03, P < 0. 05 ). Increased serum perfluorooctane sulfate (PFOS) concentrations were associated with increased blood insulin (0.14 +/- 0.05, P < 0.01), homeostasis model assessment of insulin resistance (0.14 0.05, P < 0.01), and beta-cell function (0.15 +/- 0.05, P < 0.01). Serum PFOS concentrations were also unfavorably correlated with serum HDL cholesterol (OR 1.61 [95% Cl 1.15-2.26], P < 0.05). CONCLUSIONS - Serum PFCs were associated with glucose homeostasis and indicators of metabolic syndrome. Further clinical and animal studies are warranted to clarify putative causal relationships

Jet quenching in shock waves

We study the propagation of an ultrarelativistic light quark jet inside a shock wave using the holographic principle. The maximum stopping distance and its dependency on the energy of the jet is obtained

The role of the initial surface density profiles of the disc on giant planet formation: comparing with observations

In order to explain the main characteristics of the observed population of extrasolar planets and the giant planets in the Solar System, we need to get a clear understanding of which are the initial conditions that allowed their formation. To this end we develop a semi-analytical model for computing planetary systems formation based on the core instability model for the gas accretion of the embryos and the oligarchic growth regime for the accretion of the solid cores. With this model we explore not only different initial discs profiles motivated by similarity solutions for viscous accretion discs, but we also consider different initial conditions to generate a variety of planetary systems assuming a large range of discs masses and sizes according to the last results in protoplanetary discs observations. We form a large population of planetary systems in order to explore the effects in the formation of assuming different discs and also the effects of type I and II regimes of planetary migration, which were found to play fundamental role in reproducing the distribution of observed exoplanets. Our results show that the observed population of exoplanets and the giant planets in the Solar System are well represented when considering a surface density profile with a power law in the inner part characterized by an exponent of -1, which represents a softer profile when compared with the case most similar to the MMSN model case.Comment: 14 pages, 12 figures, MNRAS, 412, 211

The role of the initial surface density profiles of the disc on giant planet formation: comparing with observations

In order to explain the main characteristics of the observed population of extrasolar planets and the giant planets in the Solar System, we need to get a clear understanding of which are the initial conditions that allowed their formation. To this end we develop a semi-analytical model for computing planetary systems formation based on the core instability model for the gas accretion of the embryos and the oligarchic growth regime for the accretion of the solid cores. With this model we explore not only different initial discs profiles motivated by similarity solutions for viscous accretion discs, but we also consider different initial conditions to generate a variety of planetary systems assuming a large range of discs masses and sizes according to the last results in protoplanetary discs observations. We form a large population of planetary systems in order to explore the effects in the formation of assuming different discs and also the effects of type I and II regimes of planetary migration, which were found to play fundamental role in reproducing the distribution of observed exoplanets. Our results show that the observed population of exoplanets and the giant planets in the Solar System are well represented when considering a surface density profile with a power law in the inner part characterized by an exponent of -1, which represents a softer profile when compared with the case most similar to the MMSN model case.Comment: 14 pages, 12 figures, MNRAS, 412, 211

Landau levels in the case of two degenerate coupled bands: kagome lattice tight-binding spectrum

The spectrum of charged particles hopping on a kagome lattice in a uniform transverse magnetic field shows an unusual set of Landau levels at low field. They are unusual in two respects: the lowest Landau levels are paramagnetic so their energies decrease linearly with increasing field magnitude, and the spacings between the levels are not equal. These features are shown to follow from the degeneracy of the energy bands in zero magnetic field. We give a general discussion of Landau levels in the case of two degenerate bands, and show how the kagome lattice tight-binding model includes one special case of this more general problem. We also discuss the consequences of this for the behavior of the critical temperature of a kagome grid superconducting wire network, which is the experimental system that originally motivated this work.Comment: 18 pages, 8 figure