Simultaneous Multiple Surface Segmentation Using Deep Learning

The task of automatically segmenting 3-D surfaces representing boundaries of objects is important for quantitative analysis of volumetric images, and plays a vital role in biomedical image analysis. Recently, graph-based methods with a global optimization property have been developed and optimized for various medical imaging applications. Despite their widespread use, these require human experts to design transformations, image features, surface smoothness priors, and re-design for a different tissue, organ or imaging modality. Here, we propose a Deep Learning based approach for segmentation of the surfaces in volumetric medical images, by learning the essential features and transformations from training data, without any human expert intervention. We employ a regional approach to learn the local surface profiles. The proposed approach was evaluated on simultaneous intraretinal layer segmentation of optical coherence tomography (OCT) images of normal retinas and retinas affected by age related macular degeneration (AMD). The proposed approach was validated on 40 retina OCT volumes including 20 normal and 20 AMD subjects. The experiments showed statistically significant improvement in accuracy for our approach compared to state-of-the-art graph based optimal surface segmentation with convex priors (G-OSC). A single Convolution Neural Network (CNN) was used to learn the surfaces for both normal and diseased images. The mean unsigned surface positioning errors obtained by G-OSC method 2.31 voxels (95% CI 2.02-2.60 voxels) was improved to $1.27$ voxels (95% CI 1.14-1.40 voxels) using our new approach. On average, our approach takes 94.34 s, requiring 95.35 MB memory, which is much faster than the 2837.46 s and 6.87 GB memory required by the G-OSC method on the same computer system.Comment: 8 page

Gravitational Wave Background from Phantom Superinflation

Recently, the early superinflation driven by phantom field has been proposed and studied. The detection of primordial gravitational wave is an important means to know the state of very early universe. In this brief report we discuss in detail the gravitational wave background excited during the phantom superinflation.Comment: 3 pages, 2 eps figures, to be published in PRD, revised with published version, refs. adde

Effect of the attachment of ferromagnetic contacts on the conductivity and giant magnetoresistance of graphene nanoribbons

Carbon-based nanostructures and graphene, in particular, evoke a lot of interest as new promising materials for nanoelectronics and spintronics. One of the most important issue in this context is the impact of external electrodes on electronic properties of graphene nanoribbons (GNR). The present theoretical method is based on the tight-binding model and a modified recursive procedure for Green's functions. The results show that within the ballistic transport regime, the so called end-contacted geometry (of minimal GNR/electrode interface area), is usually more advantageous for practical applications than its side-contacted counterpart (with a larger coverage area), as far as the electrical conductivity is concerned. As regards the giant magnetoresistance coefficient, however, the situation is exactly opposite, since spin- splitting effects are more pronounced in the lower conductive side-contacted setups.Comment: 8 pages, 4 figure

The effects of Zn Impurity on the Properties of Doped Cuprates in the Normal State

We study the interplay of quantum impurity, and collective spinon and holon dynamics in Zn doped high-T$_c$ cuprates in the normal state. The two-dimensional t-t$^{\prime}$-J models with one and a small amount of Zn impurity are investigated within a numerical method based on the double-time Green function theory. We study the inhomogeneities of holon density and antiferromagnetic correlation background in cases with different Zn concentrations, and obtain that doped holes tend to assemble around the Zn impurity with their mobility being reduced. Therefore a bound state of holon is formed around the nonmagnetic Zn impurity with the effect helping Zn to introduce local antiferromagnetism around itself. The incommensurate peaks we obtained in the spin structure factor indicate that Zn impurities have effects on mixing the q=($\pi$, $\pi$) and q=0 components in spin excitations.Comment: 5 pages, 3 figure

High efficiency photon counting using stopped light

Single-photon detection and photon counting play a central role in a large number of quantum communication and computation protocols. While the efficiency of state-of-the-art photo-detectors is well below the desired limits, quantum state measurements in trapped ions can be carried out with efficiencies approaching 100%. Here, we propose a method that can in principle achieve ideal photon counting, by combining the techniques of photonic quantum memory and ion-trap fluorescence detection: after mapping the quantum state of a propagating light pulse onto metastable collective excitations of a trapped cold atomic gas, it is possible to monitor the resonance fluorescence induced by an additional laser field that only couples to the metastable excited state. Even with a photon collection/detection efficiency as low as 10%, it is possible to achieve photon counting with efficiency approaching 100%.Comment: 4 page

Giant Nonlocality near the Dirac Point in Graphene

Transport measurements have been a powerful tool for uncovering new electronic phenomena in graphene. We report nonlocal measurements performed in the Hall bar geometry with voltage probes far away from the classical path of charge flow. We observe a large nonlocal response near the Dirac point in fields as low as 0.1T, which persists up to room temperature. The nonlocality is consistent with the long-range flavor currents induced by lifting of spin/valley degeneracy. The effect is expected to contribute strongly to all magnetotransport phenomena near the neutrality point

Quark-Meson Coupling Model for a Nucleon

The quark-meson coupling model for a nucleon is considered. The model describes a nucleon as an MIT bag, in which quarks are coupled to scalar and vector mesons. A set of coupled equations for the quark and the meson fields are obtained and are solved in a self-consistent way. It is shown that the mass of a nucleon as a dressed MIT bag interacting with sigma- and omega-meson fields significantly differs from the mass of a free MIT bag. A few sets of model parameters are obtained so that the mass of a dressed MIT bag becomes the nucleon mass. The results of our calculations imply that the self-energy of the bag in the quark-meson coupling model is significant and needs to be considered in doing the nuclear matter calculations.Comment: 3 figure