2,517 research outputs found
Deep Learning-Based Super-Resolution Applied to Dental Computed Tomography
The resolution of dental computed tomography
(CT) images is limited by detector geometry, sensitivity, patient movement, the reconstruction technique and the need to minimize radiation dose. Recently, the use of convolutional neural network
(CNN) architectures has shown promise as a resolution enhancement method. In the current work, two CNN architectures—a subpixel network and the so called U-net—have been considered for the resolution enhancement of 2-D cone-beam CT image slices
of ex vivo teeth. To do so, a training set of 5680 cross-sectional slices of 13 teeth and a test set of 1824 slices of 4 structurally different teeth were used. Two existing reconstruction-based super-resolution methods using l2-norm and total variation regularization were used for comparison. The results were evaluated with different metrics (peak signal-to-noise ratio, structure similarity index, and other objective measures estimating human perception) and subsequent image-segmentation-based analysis.
In the evaluation, micro-CT images were used as ground truth.The results suggest the superiority of the proposed CNN-based approaches over reconstruction-based methods in the case of dental CT images, allowing better detection of medically salient features, such as the size, shape, or curvature of the root canal
The bouncing dynamics of inertial self-propelled particles reveals directional asymmetry
The paper is devoted to the study of experimental conditions for bound states
in which active particles are forced by their environment to move forward and
backward in a steady oscillatory mode. The realization of this idea in our
proposal is carried out by means of a hexbug (a vibrating self-propelled toy
robot) confined in a narrow channel bounded by a rigid moving end-wall. The
motion modes were studied both experimentally and theoretically. In the
theoretical framework, we investigated the one-dimensional single-particle
approximation within the Brownian model of active particles with inertia using
numerical simulations. The model includes the hexbug's contact with the base
plate via tilted flexible legs that provide propulsion. At the same time, the
tilting contributes to directional asymmetry of the system. The end-wall
velocity was used as an external parameter to influence the bouncing process.
After regressing the spatial and temporal statistical characteristics, the
simulation satisfactorily reproduced the experimental properties of hexbug
motion, mainly due to the considered directional asymmetry
The distance-based approach to the quantification of the world convergences and imbalances - comparisons across countries and factors
The paper presents a general empirical method of distance-based multifaceted systematic identifying
of the positions of countries in relation to inequalities and imbalances. In order to understand the world economic relations in their entirety, we decided to analyze twelve most populous countries and eleven macroeconomic, environmental and demographic indicators relevant to them. Our analysis covering the period 1992-2008 attempts to identify core parts of the global economic system and countries that pose a potential risk of instability
Magnetic dot arrays modeling via the system of the radial basis function networks
Two dimensional square lattice general model of the magnetic dot array is
introduced. In this model the intradot self-energy is predicted via the neural
network and interdot magnetostatic coupling is approximated by the collection
of several dipolar terms. The model has been applied to disk-shaped cluster
involving 193 ultrathin dots and 772 interaction centers. In this case among
the intradot magnetic structures retrieved by neural networks the important
role play single-vortex magnetization modes. Several aspects of the model have
been understood numerically by means of the simulated annealing method.Comment: 16 pages, 8 figure
Assessing the Viscoelasticity of Photopolymer Nanowires Using a Three-Parameter Solid Model for Bending Recovery Motion
Photopolymer nanowires prepared by two-photon polymerization direct laser writing (TPP-DLW) are the building blocks of many microstructure systems. These nanowires possess viscoelastic characteristics that define their deformations under applied forces when operated in a dynamic regime. A simple mechanical model was previously used to describe the bending recovery motion of deflected nanowire cantilevers in Newtonian liquids. The inverse problem is targeted in this work; the experimental observations are used to determine the nanowire physical characteristics. Most importantly, based on the linear three-parameter solid model, we derive explicit formulas to calculate the viscoelastic material parameters. It is shown that the effective elastic modulus of the studied nanowires is two orders of magnitude lower than measured for the bulk material. Additionally, we report on a notable effect of the surrounding aqueous glucose solution on the elasticity and the intrinsic viscosity of the studied nanowires made of Ormocomp
- …