Shear-Warp Algorithm Research Articles

Universal simulation of absorption effects for X-ray diffraction in reflection geometry.

Analytical calculations of absorption corrections for X-ray powder diffraction experiments on non-ideal samples with surface roughness, porosity or absorption contrasts from multiple phases require complex mathematical models to represent their material distribution. In a computational approach to this problem, a practicable ray-tracing algorithm is formulated which is capable of simulating angle-dependent absorption corrections in reflection geometry for any given rasterized sample model. Single or multiphase systems with arbitrary surface roughness, porosity and spatial distribution of the phases in any combination can be modeled on a voxel grid by assigning respective values to each voxel. The absorption corrections are calculated by tracing the attenuation of X-rays along their individual paths via a modified shear-warp algorithm. The algorithm is presented in detail and the results of simulated absorption corrections on samples with various surface modulations are discussed in the context of published experimental results.

CPU-based speed acceleration techniques for shear warp volume rendering

The shear-warp algorithm with run-length-encoded volume is one of the fastest CPU-based speed acceleration techniques developed so far for direct volume rendering. But it has some defects, such as the increases in memory consumption and preprocessing time as well as the deterioration in image quality. This paper provides two kinds of techniques that can solve such defects without degrading rendering speed. One technique concentrates on enhancing image quality and decreasing memory consumption without reducing rendering speed, by making direct access to the memory space where initially loaded volume data is stored. The other technique concentrates on accelerating rendering speed and decreasing preprocessing time, by creating only one run-length-encoded volume and by combining non-photorealistic rendering techniques with shear-warp algorithm. In the present research, both techniques efficiently decreased the memory consumption and preprocessing time of shear-warp algorithm. They also showed optimal results in rendering speed and image quality.

Automatic registration and fast volume reconstruction from serial histology sections

The scope of this research is to propose a novel method for automatic registration and fast volume reconstruction of serial tissue sections based on common-configured computer, on the premise that the algorithm can achieve accurate result with fast speed and little interaction as much as possible. The whole flowchart comprises the four main parts, of which image registration and image reconstruction are of great significance, materialized the following innovative ideas. Firstly, mutual information measure is combined with morphological gradient information to contain fewer erroneous maxima and lead to the global maximum when registration. Secondly, the hybrid optimizer combined Particle Swarm Optimization (PSO) with Powell algorithm is proposed to restrain local maxima of mutual information function and to improve the registration accuracy. Thirdly, the multiresolution data structure based on Mallat decomposition not only improves the behavior of registration function, but also accelerates the algorithm speed. Finally, an improved Shear–Warp algorithm is proposed based on the sorted volumetric dataset for registered image stack, which can skip all of the transparent voxels and achieve faster speed. Experimental results demonstrate that the novel registration and reconstruction algorithms are effective and efficient to achieve the virtual three-dimensional gekko’s cervical spinal cord successfully and the reconstruction result can be rotated, scaled, incised and measured arbitrarily, which is valuable to be applied to the other kinds of serial histology sections.

An optical model for translucent volume rendering and its implementation using the preintegrated shear-warp algorithm.

In order to efficiently and effectively reconstruct 3D medical images and clearly display the detailed information of inner structures and the inner hidden interfaces between different media, an Improved Volume Rendering Optical Model (IVROM) for medical translucent volume rendering and its implementation using the preintegrated Shear-Warp Volume Rendering algorithm are proposed in this paper, which can be readily applied on a commodity PC. Based on the classical absorption and emission model, effects of volumetric shadows and direct and indirect scattering are also considered in the proposed model IVROM. Moreover, the implementation of the Improved Translucent Volume Rendering Method (ITVRM) integrating the IVROM model, Shear-Warp and preintegrated volume rendering algorithm is described, in which the aliasing and staircase effects resulting from under-sampling in Shear-Warp, are avoided by the preintegrated volume rendering technique. This study demonstrates the superiority of the proposed method.

The parallelized perspective shear-warp algorithm for volume rendering

The shear-warp algorithm for volume rendering is among the fastest volume rendering algorithms. It is an object-order algorithm, based on the idea of the factorization of the view matrix into a 3D shear and a 2D warp component. Thus, the compositing can be done in sheared object space, which allows the algorithm to take advantage of data locality. Although the idea of a perspective projection shear-warp algorithm is not new, it is not widely used so far. That may be because it is slower than the parallel projection algorithm and often slower than hardware supported approaches. In this paper, we present a new parallelized version of the perspective shear-warp algorithm. The parallelized algorithm was designed for distributed memory machines using MPI. The new algorithm takes advantage of the idea that the warp can be done in most computers’ graphics hardware very fast, so that the remote parallel computer only needs to do the compositing. Our algorithm uses this idea to do the compositing on the remote machine, which transfers the resulting 2D intermediate image to the display machine. Even though the display machine can be a mid range PC or laptop computer, it can be used to display complex volumetric data, provided there is a network connection to a high performance parallel computer. Furthermore, remote rendering could be used to drive virtual environments, which typically require perspective projection and high frame rates for stereo projection and multiple screens.

Combined 3D visualization of volume data and polygonal models using a Shear-Warp algorithm

Shear-Warp techniques provide an efficient way to perform the projection and blending stages of the volume-rendering process. They treat volume-data slices in a coherent order and can be naturally integrated with the Z-Buffer algorithm. The present paper presents a study on the integration between Shear-Warp and Z-Buffer, and extends the Shear-Warp algorithm to handle scenes composed of both volume and polygonal data. We present methods to handle opaque/translucent volumes combined with opaque/translucent polygonal models. As volume data usually has a different resolution from that of the final image, in which Z-Buffer renders the polygonal data, several variants for this integration are analyzed. Results are shown to support some conclusions on the trade-off quality versus time that can be expected.

Communications Optimizations and Efficient Load-Balancing for a Volume Rendering Algorithm on a Cluster of PCs

In the medical field, volume rendering provides good quality 3D visualizations but it is still not interactive enough for a day-to-day practice. The most efficient sequential algorithm is the Shear-Warp algorithm. It renders up to 10 images per second for a small dataset. The goal of this paper is to present an efficient parallel implementation of the Shear-Warp algorithm for a distributed memory architecture, a cluster of PCs connected with a high speed network. This highly irregular algorithm led us to implement a dynamic load balancing algorithm. Furthermore, to reduce the overhead due to data redistribution, we overlap communications with computations using MPI's asynchronous communications. Using a good load-balancing and communication overlap, our implementation generates real-time 3D medical images with a good quality and a high resolution.

Extensions to permutation warping for parallel volume rendering

Biomedical volume visualization requires high quality and high performance, but the existing high performance solutions such as the Shear Warp algorithm, 3D texture mapping, and special purpose hardware have problems. Permutation warping achieves high fidelity for biomedical datasets of regular rectilinear volumes, using a one-to-one communication scheme for optimal O(1) communication on massively parallel computers. Extensions are presented including data dependent optimizations using octrees, arbitrary view angle flexibility, and multiple instruction stream multiple data stream (MIMD) implementation. A MasPar MP-2, single instruction stream multiple data stream (SIMD) (16,384 processor), implementation achieves 14 frames/s, using trilinear reconstruction on 128 3 volumes for 400% runtime improvement over our previous result. A Proteus MIMD (32 processor) implementation achieves 1 frame/s on the same data. Additionally the PermWeb software architecture is presented, that has been shown as a proof of concept means to provide wide shared access to a powerful centralized renderer. All of these improvements make permutation warping an effective solution for biomedial volume visualization.