141 research outputs found

    A Multi-Resolution Interactive Previewer for Volumetric Data on Arbitary Meshes

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    In this paper we describe a rendering method suitable for interactive previewing of large-scale arbitary-mesh volume data sets. A data set to be visualized is represented by a ''point cloud,'' i. e., a set of points and associated data values without known connectivity between the points. The method uses a multi-resolution approach to achieve interactive rendering rates of several frames per second for arbitrarily large data sets. Lower-resolution approximations of an original data set are created by iteratively applying a point- decimation operation to higher-resolution levels. The goal of this method is to provide the user with an interactive navigation and exploration tool to determine good viewpoints and transfer functions to pass on to a high-quality volume renderer that uses a standard algorithm

    Dynamic view-dependent visualization of unstructured tetrahedral volumetric meshes

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    Visualization of large volumetric datasets has always been an important problem. Due to the high computational requirements of volume-rendering techniques, achieving interactive rates is a real challenge. We present a selective refinement scheme that dynamically refines the mesh according to the camera parameters. This scheme automatically determines the impact of different parts of the mesh on the output image and refines the mesh accordingly, without needing any user input. The view-dependent refinement scheme uses a progressive mesh representation that is based on an edge collapse-based tetrahedral mesh simplification algorithm. We tested our view-dependent refinement framework on an existing state-of-theart volume renderer. Thanks to low overhead dynamic view-dependent refinement, we achieve interactive frame rates for rendering common datasets at decent image resolutions. © 2012 The Visualization Society of Japan

    Patient specific numerical simulation of flow in the human upper airways for assessing the effect of nasal surgery

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    The study is looking into the potential of using computational fluid dynamics (CFD) as a tool for predicting the outcome of surgery for alleviation of obstructive sleep apnea syndrome (OSAS). From pre- and post-operative computed tomography (CT) of an OSAS patient, the pre- and post-operative geometries of the patient's upper airways were generated. CFD simulations of laminar flow in the patient's upper airway show that after nasal surgery the mass flow is more evenly distributed between the two nasal cavities and the pressure drop over the nasal cavity has increased. The pressure change is contrary to clinical measurements that the CFD results have been compared with, and this is most likely related to the earlier steps of modelling - CT acquisition and geometry retrieval.Comment: Proceedings of the 12th International Conference on CFD in Oil & Gas, Metallurgical and Process Industries, Trondheim, Norway, May 30th - June 1st, 2017, 11 pages, 13 figure

    Optimum Slice Reduction Algorithm For Fast Surface Reconstruction From Contour Slices

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    Tesis ini memfokus kepada pembinaan semula permukaan daripada siri hirisan kontur, dengan tujuan mempercepatkan proses pembinaan semula di samping mengekalkan kualiti output pada tahap yang boleh diterima. This thesis is concerned with the reconstruction of surface from a series of contour slices, with the aim to speed up the reconstruction process while preserving the output quality at an acceptable level

    Optimum Slice Reduction Algorithm For Fast Surface Reconstruction From Contour slices [QA571. T164 2007 f rb].

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    Tesis ini memfokus kepada pembinaan semula permukaan daripada siri hirisan kontur, dengan tujuan mempercepatkan proses pembinaan semula di samping mengekalkan kualiti output pada tahap yang boleh diterima. Teknik yang dicadangkan dalam tesis ini memproses hirisan-hirisan kontur sebelum pembinaan semula permukaan. This thesis is concerned with the reconstruction of surface from a series of contour slices, with the aim to speed up the reconstruction process while preserving the output quality at an acceptable level. The proposed technique in this thesis, preprocesses the slices of contour prior to surface reconstruction

    Techniques for Large Data Visualization

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    pages 315-32

    Volumetric rendering techniques for scientific visualization

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    Ankara : The Department of Computer Engineering and The Graduate School of Engineering and Science of Bilkent University, 2014.Thesis (Ph.D.) -- Bilkent University, 2014.Includes bibliographical references leaves 80-86.Direct volume rendering is widely used in many applications where the inside of a transparent or a partially transparent material should be visualized. We have explored several aspects of the problem. First, we proposed a view-dependent selective refinement scheme in order to reduce the high computational requirements without affecting the image quality significantly. Then, we explored the parallel implementations of direct volume rendering: both on GPU and on multi-core systems. Finally, we used direct volume rendering approaches to create a tool, MaterialVis, to visualize amorphous and/or crystalline materials. Visualization of large volumetric datasets has always been an important problem. Due to the high computational requirements of volume-rendering techniques, achieving interactive rates is a real challenge. We present a selective refinement scheme that dynamically refines the mesh according to the camera parameters. This scheme automatically determines the impact of different parts of the mesh on the output image and refines the mesh accordingly, without needing any user input. The viewdependent refinement scheme uses a progressive mesh representation that is based on an edge collapse-based tetrahedral mesh simplification algorithm. We tested our view-dependent refinement framework on an existing state-of-the-art volume renderer. Thanks to low overhead dynamic view-dependent refinement, we achieve interactive frame rates for rendering common datasets at decent image resolutions. Achieving interactive rates for direct volume rendering of large unstructured volumetric grids is a challenging problem, but parallelizing direct volume rendering algorithms can help achieve this goal. Using Compute Unified Device Architecture (CUDA), we propose a GPU-based volume rendering algorithm that itself is based on a cell projection-based ray-casting algorithm designed for CPU implementations. We also propose a multi-core parallelized version of the cell-projection algorithm using OpenMP. In both algorithms, we favor image quality over rendering speed. Our algorithm has a low memory footprint, allowing us to render large datasets. Our algorithm support progressive rendering. We compared the GPU implementation with the serial and multi-core implementations. We observed significant speed-ups, that, together with progressive rendering, enabling reaching interactive rates for large datasets. Visualization of materials is an indispensable part of their structural analysis. We developed a visualization tool for amorphous as well as crystalline structures, called MaterialVis. Unlike the existing tools, MaterialVis represents material structures as a volume and a surface manifold, in addition to plain atomic coordinates. Both amorphous and crystalline structures exhibit topological features as well as various defects. MaterialVis provides a wide range of functionality to visualize such topological structures and crystal defects interactively. Direct volume rendering techniques are used to visualize the volumetric features of materials, such as crystal defects, which are responsible for the distinct fingerprints of a specific sample. In addition, the tool provides surface visualization to extract hidden topological features within the material. Together with the rich set of parameters and options to control the visualization, MaterialVis allows users to visualize various aspects of materials very efficiently as generated by modern analytical techniques such as the Atom Probe Tomography.Okuyan, ErhanPh.D
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