Research on Improved Ray Casting Algorithm and Its Application in Three-Dimensional Reconstruction

Spinal pathology treatment has become an urgent issue to be solved. How to effectively prevent and treat spinal pathology has become a research hotspot in the field of surgery. Aiming at the problem of too long volume rendering time caused by the trilinear interpolation sampling method in the reconstruction and visualization of the vertebra 3D model, an improved ray projection algorithm is proposed to quickly reconstruct a 3D vertebra model from medical CT vertebra images. This method first classifies CT data, assigns corresponding color values and opacity transfer functions to different types of data, and then uses inverse distance-weighted interpolation (IDWI) sampling to replace the trilinear interpolation sampling method for the voxel where the sampling point is located to accelerate the interpolation operation. The color value and opacity of the sampling points are obtained, and finally, the attributes of all the sampling points are synthesized and calculated to obtain the final rendering effect, and the reconstruction of the three-dimensional vertebra model is completed. Experimental results show that the proposed method not only can obtain higher quality rendered images but also has a certain improvement in rendering speed compared with traditional algorithms.

Scaling Up and Down of 3-D Floating-point Data in Quantum Computation

In the past few decades, quantum computation has become increasingly attractivedue to its remarkable performance. Quantum image scaling is considered a common geometric transformation in quantum image processing, however, the quantum floating-point data version of which does not exist. Is there a corresponding scaling for 2-D and 3-D floating-point data? The answer is yes.In this paper, we present quantum scaling up and down scheme for floating-point data by using trilinear interpolation method in 3-D space. This scheme offers better performance (in terms of the precision of floating-point numbers) for realizing the quantum floating-point algorithms compared to previously classical approaches. The Converter module we proposed can solve the conversion of fixed-point numbers to floating-point numbers of arbitrary size data with p + q qubits based on IEEE-754 format, instead of 32-bit single-precision, 64-bit double precision or 128-bit extended-precision. Usually, we use nearest neighbor interpolation and bilinear interpolation to achieve quantum image scaling algorithms, which are not applicable in high-dimensional space. This paper proposes trilinear interpolation of floating-point numbers in 3-D space to achieve quantum algorithms of scaling up and down for 3-D floating-point data. Finally, the circuits of quantum scaling up and down for 3-D floating-point data are designed.

Fortran Coarray Implementation of Semi-Lagrangian Convected Air Particles within an Atmospheric Model

This work added semi-Lagrangian convected air particles to the Intermediate Complexity Atmospheric Research (ICAR) model. The ICAR model is a simplified atmospheric model using quasi-dynamical downscaling to gain performance over more traditional atmospheric models. The ICAR model uses Fortran coarrays to split the domain amongst images and handle the halo region communication of the image’s boundary regions. The newly implemented convected air particles use trilinear interpolation to compute initial properties from the Eulerian domain and calculate humidity and buoyancy forces as the model runs. This paper investigated the performance cost and scaling attributes of executing unsaturated and saturated air particles versus the original particle-less model. An in-depth analysis was done on the communication patterns and performance of the semi-Lagrangian air particles, as well as the performance cost of a variety of initial conditions such as wind speed and saturation mixing ratios. This study found that given a linear increase in the number of particles communicated, there is an initial decrease in performance, but that it then levels out, indicating that over the runtime of the model, there is an initial cost of particle communication, but that the computational benefits quickly offset it. The study provided insight into the number of processors required to amortize the additional computational cost of the air particles.

3D Spatial Interpolation Methods for Open-Pit Mining Air Quality with Data Acquired by Small UAV Based Monitoring System

Open-pit mining activities, including blasting, drilling, loading, and transport, often result in the direct emission of particulates and gases into the atmosphere. Occupational exposure to these pollutants is considered as the risk for health, especially the risk of developing respiratory diseases. An air quality monitoring system and spatial analysis are necessary to identify these potential hazards. In this study, we propose an air quality monitoring system that integrates gas and dust sensors into a small multi-rotor copter or unmanned aerial vehicle (UAV). Different spatial interpolation methods including trilinear interpolation, nearest neighbour, and natural neighbour applied to the monitoring data (CO, SO2, PM2.5, CO2) from our system to derive air concentration levels in the atmosphere of open-pit coal mines were also examined. The results show that the UAV based air quality monitoring system performed efficiently and safely in conditions of deep open-pit coal mines. In addition, for the estimation of the concentration level of gases and dust in unsampled points, trilinear interpolation performed with the most accurate result, followed by natural neighbor and nearest neighbor.

Extracting Information about the Rotator Cuff from Magnetic Resonance Images Using Deterministic and Random Techniques

We consider some methods to extract information about the rotator cuff based on magnetic resonance images; the study aims to define an alternative method of display that might facilitate the detection of partial tears in the supraspinatus tendon. Specifically, we are going to use families of ellipsoidal triangular patches to cover the humerus head near the affected area. These patches are going to be textured and displayed with the information of the magnetic resonance images using the trilinear interpolation technique. For the generation of points to texture each patch, we propose a new method that guarantees the uniform distribution of its points using a random statistical method. Its computational cost, defined as the average computing time to generate a fixed number of points, is significantly lower as compared with deterministic and other standard statistical techniques.