19,457 research outputs found

    Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs)

    Full text link
    Positron emission tomography (PET) image synthesis plays an important role, which can be used to boost the training data for computer aided diagnosis systems. However, existing image synthesis methods have problems in synthesizing the low resolution PET images. To address these limitations, we propose multi-channel generative adversarial networks (M-GAN) based PET image synthesis method. Different to the existing methods which rely on using low-level features, the proposed M-GAN is capable to represent the features in a high-level of semantic based on the adversarial learning concept. In addition, M-GAN enables to take the input from the annotation (label) to synthesize the high uptake regions e.g., tumors and from the computed tomography (CT) images to constrain the appearance consistency and output the synthetic PET images directly. Our results on 50 lung cancer PET-CT studies indicate that our method was much closer to the real PET images when compared with the existing methods.Comment: 9 pages, 2 figure

    A cooperative feature gene extraction algorithm that combines classification and clustering

    Get PDF
    In feature gene selection, filtering model concerns classification accuracy while ignoring gene redundancy problem. On the other hand, gene clustering finds correlated genes without considering their predictive abilities. It is valuable to enhance their performances by the help of each other. We report a new feature gene extraction algorithm, namely Double-thresholding Extraction of Feature Gene (DEFG), that combines gene filtering and gene clustering. It firstly pre-select feature gene set from the original dataset. A modified gene clustering is then applied to refine this set. In the gene clustering, specific designs are employed to balance the predictive abilities and the redundancies of the extracted feature gene. We have tested DEFG on a microarray dataset and compared its performance with that of two benchmark algorithms. The experimental results show that DEFG is superior to them in terms of internal validation accuracy and external validation accuracy. Also, DEFG can generalize the pattern structure by a small number of training samples. ©2009 IEEE.published_or_final_versio

    Crotalus atrox venom preconditioning increases plasma fibrinogen and reduces perioperative hemorrhage in a rat model of surgical brain injury.

    Get PDF
    Perioperative bleeding is a potentially devastating complication in neurosurgical patients, and plasma fibrinogen concentration has been identified as a potential modifiable risk factor for perioperative bleeding. The aim of this study was to evaluate preconditioning with Crotalus atrox venom (Cv-PC) as potential preventive therapy for reducing perioperative hemorrhage in the rodent model of surgical brain injury (SBI). C. atrox venom contains snake venom metalloproteinases that cleave fibrinogen into fibrin split products without inducing clotting. Separately, fibrinogen split products induce fibrinogen production, thereby elevating plasma fibrinogen levels. Thus, the hypothesis was that preconditioning with C. atrox venom will produce fibrinogen spilt products, thereby upregulating fibrinogen levels, ultimately improving perioperative hemostasis during SBI. We observed that Cv-PC SBI animals had significantly reduced intraoperative hemorrhage and postoperative hematoma volumes compared to those of vehicle preconditioned SBI animals. Cv-PC animals were also found to have higher levels of plasma fibrinogen at the time of surgery, with unchanged prothrombin time. Cv-PC studies with fractions of C. atrox venom suggest that snake venom metalloproteinases are largely responsible for the improved hemostasis by Cv-PC. Our findings indicate that Cv-PC increases plasma fibrinogen levels and may provide a promising therapy for reducing perioperative hemorrhage in elective surgeries

    Superfluid vs Ferromagnetic Behaviour in a Bose Gas of Spin-1/2 Atoms

    Full text link
    We study the thermodynamic phases of a gas of spin-1/2 atoms in the Hartree-Fock approximation. Our main result is that, for repulsive or weakly-attractive inter-component interaction strength, the superfluid and ferromagnetic phase transitions occur at the same temperature. For strongly-attractive inter-component interaction strength, however, the ferromagnetic phase transition occurs at a higher temperature than the superfluid phase transition. We also find that the presence of a condensate acts as an effective magnetic field that polarizes the normal cloud. We finally comment on the validity of the Hartree-Fock approximation in describing different phenomena in this system.Comment: 10 pages, 2 figure

    Note on a Micropolar Gas-Kinetic Theory

    Full text link
    The micropolar fluid mechanics and its transport coefficients are derived from the linearized Boltzmann equation of rotating particles. In the dilute limit, as expected, transport coefficients relating to microrotation are not important, but the results are useful for the description of collisional granular flow on an inclined slope. (This paper will be published in Traffic and Granular Flow 2001 edited by Y.Sugiyama and D. E. Wolf (Springer))Comment: 15 pages, 0 figure. To be published in Traffic and Granular Flow 2001 edited by Y.Sugiyama and D. E. Wolf (Springer

    A Goal-based Framework for Contextual Requirements Modeling and Analysis

    Get PDF
    Requirements Engineering (RE) research often ignores, or presumes a uniform nature of the context in which the system operates. This assumption is no longer valid in emerging computing paradigms, such as ambient, pervasive and ubiquitous computing, where it is essential to monitor and adapt to an inherently varying context. Besides influencing the software, context may influence stakeholders' goals and their choices to meet them. In this paper, we propose a goal-oriented RE modeling and reasoning framework for systems operating in varying contexts. We introduce contextual goal models to relate goals and contexts; context analysis to refine contexts and identify ways to verify them; reasoning techniques to derive requirements reflecting the context and users priorities at runtime; and finally, design time reasoning techniques to derive requirements for a system to be developed at minimum cost and valid in all considered contexts. We illustrate and evaluate our approach through a case study about a museum-guide mobile information system

    Multiple causes of interannual sea surface temperature variability in the equatorial Atlantic Ocean

    Get PDF
    The eastern equatorial Atlantic Ocean is subject to interannual fluctuations of sea surface temperatures, with climatic impacts on the surrounding continents. The dynamic mechanism underlying Atlantic temperature variability is thought to be similar to that of the El Nino/Southern Oscillation (ENSO) in the equatorial Pacific, where air-sea coupling leads to a positive feedback between surface winds in the western basin, sea surface temperature in the eastern basin, and equatorial oceanic heat content. Here we use a suite of observational data, climate reanalysis products, and general circulation model simulations to reassess the factors driving the interannual variability. We show that some of the warm events can not be explained by previously identified equatorial wind stress forcing and ENSO-like dynamics. Instead, these events are driven by a mechanism in which surface wind forcing just north of the equator induces warm ocean temperature anomalies that are subsequently advected toward the equator. We find the surface wind patterns are associated with long-lived subtropical sea surface temperature anomalies and suggest they therefore reflect a link between equatorial and subtropical Atlantic variability

    On the computation of zone and double zone diagrams

    Full text link
    Classical objects in computational geometry are defined by explicit relations. Several years ago the pioneering works of T. Asano, J. Matousek and T. Tokuyama introduced "implicit computational geometry", in which the geometric objects are defined by implicit relations involving sets. An important member in this family is called "a zone diagram". The implicit nature of zone diagrams implies, as already observed in the original works, that their computation is a challenging task. In a continuous setting this task has been addressed (briefly) only by these authors in the Euclidean plane with point sites. We discuss the possibility to compute zone diagrams in a wide class of spaces and also shed new light on their computation in the original setting. The class of spaces, which is introduced here, includes, in particular, Euclidean spheres and finite dimensional strictly convex normed spaces. Sites of a general form are allowed and it is shown that a generalization of the iterative method suggested by Asano, Matousek and Tokuyama converges to a double zone diagram, another implicit geometric object whose existence is known in general. Occasionally a zone diagram can be obtained from this procedure. The actual (approximate) computation of the iterations is based on a simple algorithm which enables the approximate computation of Voronoi diagrams in a general setting. Our analysis also yields a few byproducts of independent interest, such as certain topological properties of Voronoi cells (e.g., that in the considered setting their boundaries cannot be "fat").Comment: Very slight improvements (mainly correction of a few typos); add DOI; Ref [51] points to a freely available computer application which implements the algorithms; to appear in Discrete & Computational Geometry (available online

    Local antiferromagnetic exchange and collaborative Fermi surface as key ingredients of high temperature superconductors

    Get PDF
    Cuprates, ferropnictides and ferrochalcogenides are three classes of unconventional high-temperature superconductors, who share similar phase diagrams in which superconductivity develops after a magnetic order is suppressed, suggesting a strong interplay between superconductivity and magnetism, although the exact picture of this interplay remains elusive. Here we show that there is a direct bridge connecting antiferromagnetic exchange interactions determined in the parent compounds of these materials to the superconducting gap functions observed in the corresponding superconducting materials. High superconducting transition temperature is achieved when the Fermi surface topology matches the form factor of the pairing symmetry favored by local magnetic exchange interactions. Our result offers a principle guide to search for new high temperature superconductors.Comment: 12 pages, 5 figures, 1 table, 1 supplementary materia
    corecore