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Journal articles on the topic 'Volume ray casting'

Author: Grafiati

Published: 4 June 2021

Last updated: 2 February 2022

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1

Ledergerber, C., G. Guennebaud, M. Meyer, M. Bacher, and H. Pfister. "Volume MLS Ray Casting." IEEE Transactions on Visualization and Computer Graphics 14, no. 6 (2008): 1372–79. http://dx.doi.org/10.1109/tvcg.2008.186.

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2

Wan, Ming, Arie Kaufman, and Steve Bryson. "Optimized Interpolation for Volume Ray Casting." Journal of Graphics Tools 4, no. 1 (1999): 11–24. http://dx.doi.org/10.1080/10867651.1999.10487498.

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3

Ray, H., H. Pfister, D. Silver, and T. A. Cook. "Ray casting architectures for volume visualization." IEEE Transactions on Visualization and Computer Graphics 5, no. 3 (1999): 210–23. http://dx.doi.org/10.1109/2945.795213.

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4

Chen, Haixin, Jürgen Hesser, and Reinhard Männer. "Ray casting free-form deformed-volume objects." Journal of Visualization and Computer Animation 14, no. 2 (2003): 61–72. http://dx.doi.org/10.1002/vis.305.

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5

Liu, Li Peng, Yong Xiong Sun, Tie Jun Guan, and Li Ping Huang. "Improved Rapid Interpolation Ray Casting Algorithm." Advanced Materials Research 846-847 (November 2013): 1247–51. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1247.

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Ray casting algorithm is a kind of widely used volume rendering algorithm in the field of medical 3D reconstruction. One of the greatest advantages of it is the high rendering quality, while the rendering speed is rather low. In order to accelerate the rendering speed, in this paper, it proposed an accelerated ray casting algorithm which is based on the proximate cloud algorithm, combined with empty voxel leaping and fast interpolation. Meanwhile, it also analyzed the complexity of computing to significantly enhance the speed of the algorithm on volume rendering.

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6

Wan, Ming, Steve Bryson, and Arie Kaufman. "Boundary cell-based acceleration for volume ray casting." Computers & Graphics 22, no. 6 (1998): 715–22. http://dx.doi.org/10.1016/s0097-8493(98)00070-3.

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7

Wu, Kui, Aaron Knoll, Benjamin J. Isaac, Hamish Carr, and Valerio Pascucci. "Direct Multifield Volume Ray Casting of Fiber Surfaces." IEEE Transactions on Visualization and Computer Graphics 23, no. 1 (2017): 941–49. http://dx.doi.org/10.1109/tvcg.2016.2599040.

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8

LIM, S., and B. S. SHIN. "A Half-Skewed Octree for Volume Ray Casting." IEICE Transactions on Information and Systems E90-D, no. 7 (2007): 1085–91. http://dx.doi.org/10.1093/ietisy/e90-d.7.1085.

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9

Goel, Vineet, and Amar Mukherjee. "An optimal parallel algorithm for volume ray casting." Visual Computer 12, no. 1 (1996): 26–39. http://dx.doi.org/10.1007/s003710050045.

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10

Goel, Vineet, and Amar Mukherjee. "An optimal parallel algorithm for volume ray casting." Visual Computer 12, no. 1 (1996): 26–39. http://dx.doi.org/10.1007/bf01782217.

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11

Schubert, Nicole, and Ingrid Scholl. "Comparing GPU-based multi-volume ray casting techniques." Computer Science - Research and Development 26, no. 1-2 (2010): 39–50. http://dx.doi.org/10.1007/s00450-010-0141-1.

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12

Kim, Jusub, and Joseph JaJa. "Streaming Model Based Volume Ray Casting Implementation for Cell Broadband Engine." Scientific Programming 17, no. 1-2 (2009): 173–84. http://dx.doi.org/10.1155/2009/248465.

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Interactive high quality volume rendering is becoming increasingly more important as the amount of more complex volumetric data steadily grows. While a number of volumetric rendering techniques have been widely used, ray casting has been recognized as an effective approach for generating high quality visualization. However, for most users, the use of ray casting has been limited to datasets that are very small because of its high demands on computational power and memory bandwidth. However the recent introduction of the Cell Broadband Engine (Cell B.E.) processor, which consists of 9 heterogen

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13

Mehaboobathunnisa, R., A. A. Haseena Thasneem, and M. Mohamed Sathik. "Fuzzy Mutual Information-Based Intraslice Grouped Ray Casting." Journal of Intelligent Systems 28, no. 1 (2019): 77–86. http://dx.doi.org/10.1515/jisys-2016-0263.

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Abstract The traditional ray casting algorithm has the capability to render three-dimensional volume data in the viewable two-dimensional form by sampling the color data along the rays. The speed of the technique relies on the computation incurred by the huge volume of rays. The objective of the paper is to reduce the computations made over the rays by eventually reducing the number of samples being processed throughout the volume data. The proposed algorithm incorporates the grouping strategy based on fuzzy mutual information (FMI) over a group of voxels in the conventional ray casting to ach

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14

채수평 and Shin Byeong Seok. "Accelerating GPU-based Volume Ray-casting Using Brick Vertex." Journal of the Korea Computer Graphics Society 17, no. 3 (2011): 1–7. http://dx.doi.org/10.15701/kcgs.2011.17.3.1.

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15

Knoll, Aaron, Ingo Wald, Paul Navratil, et al. "RBF Volume Ray Casting on Multicore and Manycore CPUs." Computer Graphics Forum 33, no. 3 (2014): 71–80. http://dx.doi.org/10.1111/cgf.12363.

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16

Knoll, A., Y. Hijazi, R. Westerteiger, M. Schott, C. Hansen, and H. Hagen. "Volume Ray Casting with Peak Finding and Differential Sampling." IEEE Transactions on Visualization and Computer Graphics 15, no. 6 (2009): 1571–78. http://dx.doi.org/10.1109/tvcg.2009.204.

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17

Byeonghun Lee, Jihye Yun, Jinwook Seo, Byonghyo Shim, Yeong-Gil Shin, and Bohyoung Kim. "Fast High-Quality Volume Ray Casting with Virtual Samplings." IEEE Transactions on Visualization and Computer Graphics 16, no. 6 (2010): 1525–32. http://dx.doi.org/10.1109/tvcg.2010.155.

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18

Nagae, Takanori, and Hiroshi Nagahashi. "Accelerated Volume Ray Casting using a Pair of Depth Maps." Journal of the Institute of Image Information and Television Engineers 53, no. 5 (1999): 758–64. http://dx.doi.org/10.3169/itej.53.758.

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19

김민호 and 이영준. "Real-time BCC Volume Isosurface Ray Casting on the GPU." Journal of the Korea Computer Graphics Society 18, no. 4 (2012): 25–34. http://dx.doi.org/10.15701/kcgs.2012.18.4.25.

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20

Rossler, F., R. P. Botchen, and T. Ertl. "Dynamic Shader Generation for GPU-Based Multi-Volume Ray Casting." IEEE Computer Graphics and Applications 28, no. 5 (2008): 66–77. http://dx.doi.org/10.1109/mcg.2008.96.

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21

Schlegel, P., M. Makhinya, and R. Pajarola. "Extinction-Based Shading and Illumination in GPU Volume Ray-Casting." IEEE Transactions on Visualization and Computer Graphics 17, no. 12 (2011): 1795–802. http://dx.doi.org/10.1109/tvcg.2011.198.

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22

Wang, Huadeng, Guang Xu, Xipeng Pan, Zhenbing Liu, Rushi Lan, and Xiaonan Luo. "A Novel Ray-Casting Algorithm Using Dynamic Adaptive Sampling." Wireless Communications and Mobile Computing 2020 (October 13, 2020): 1–12. http://dx.doi.org/10.1155/2020/8822624.

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Ray-casting algorithm is an important volume rendering algorithm, which is widely used in medical image processing. Aiming to address the shortcomings of the current ray-casting algorithms in 3D reconstruction of medical images, such as slow rendering speed and low sampling efficiency, an improved algorithm based on dynamic adaptive sampling is proposed. By using the central difference gradient method, the corresponding sampling interval is obtained dynamically according to the different sampling points. Meanwhile, a new rendering operator is proposed based on the color value and opacity chang

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23

Leu, M. C., S. H. Park, and K. K. Wang. "Geometric Representation of Translational Swept Volumes and its Applications." Journal of Engineering for Industry 108, no. 2 (1986): 113–19. http://dx.doi.org/10.1115/1.3187045.

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This paper presents a method for representing the geometries of translational swept volumes of three-dimensional objects which can be constructed by the union of three types of primitive objects: blocks, cylinders, and spheres. The representation method involves three major steps. First, the swept volume of each primitive object is modeled by a boundary representation. Second, based on ray-casting and scan-rendering methods, the boundary representation is converted into a ray in–out classification, which represents the rays entering and exiting from the primitive swept volume. Third, the ray i

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24

Meyer-Spradow, J., T. Ropinski, J. Mensmann, and K. Hinrichs. "Voreen: A Rapid-Prototyping Environment for Ray-Casting-Based Volume Visualizations." IEEE Computer Graphics and Applications 29, no. 6 (2009): 6–13. http://dx.doi.org/10.1109/mcg.2009.130.

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25

Binyahib, Roba, Tom Peterka, Matthew Larsen, Kwan-Liu Ma, and Hank Childs. "A Scalable Hybrid Scheme for Ray-Casting of Unstructured Volume Data." IEEE Transactions on Visualization and Computer Graphics 25, no. 7 (2019): 2349–61. http://dx.doi.org/10.1109/tvcg.2018.2833113.

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26

Campagnolo, Leonardo Q., and Waldemar Celes. "Interactive directional ambient occlusion and shadow computations for volume ray casting." Computers & Graphics 84 (November 2019): 66–76. http://dx.doi.org/10.1016/j.cag.2019.08.009.

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27

Bozorgi, Mohammadmehdi, and Frank Lindseth. "GPU-based multi-volume ray casting within VTK for medical applications." International Journal of Computer Assisted Radiology and Surgery 10, no. 3 (2014): 293–300. http://dx.doi.org/10.1007/s11548-014-1069-x.

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28

Ke, Hao-Ren, and Ruei-Chuan Chang. "Sample buffer: A progressive refinement ray-casting algorithm for volume rendering." Computers & Graphics 17, no. 3 (1993): 277–83. http://dx.doi.org/10.1016/0097-8493(93)90076-l.

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29

Chen, Wei, Wei Hua, HuJun Bao, and QunSheng Peng. "Real-time ray casting rendering of volume clipping in medical visualization." Journal of Computer Science and Technology 18, no. 6 (2003): 804–14. http://dx.doi.org/10.1007/bf02945470.

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30

Feng, Yin Qi, and Kun Wang. "3-D Image Reconstruction in Optical Coherence Tomography Systems Based on VTK in OCT Systems." Advanced Materials Research 459 (January 2012): 320–23. http://dx.doi.org/10.4028/www.scientific.net/amr.459.320.

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According to a ray casting algorithm，a method of 3-D image reconstruction in optical coherence tomography systems is presented. Volume data formed by a series of cross-sectional 2-D images are obtained experimentally in a traditional OCT system and a full-field OCT system. Using the ray casting algorithm, 3-D images have been reconstructed from these data base on VTK. The 3-D images rendering apparently reflect the corresponding details of samples

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31

Szalva, Péter, and Imre Norbert Orbulov. "Influence of Vacuum Support on the Fatigue Life of AlSi9Cu3(Fe) Aluminum Alloy Die Castings." Journal of Materials Engineering and Performance 29, no. 9 (2020): 5685–95. http://dx.doi.org/10.1007/s11665-020-05050-y.

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Abstract High-pressure die casting (HPDC) is a near-net-shape process that produces high quality castings with narrow dimensional tolerances. The HPDC castings are being increasingly used due to good flexibility and high productivity, especially for the automotive industry. Depending on the location of the cast components, there are ever more complex geometries and increasing strength requirements that can be achieved by the application of vacuum-assisted die casting (VPDC). The most specific features of the HPDC process are the rapid mold filling, high cooling rate and intensification pressur

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32

Palmer, M. E., B. Totty, and S. Taylor. "Ray casting on shared-memory architectures: memory-hierarchy considerations in volume rendering." IEEE Concurrency 6, no. 1 (1998): 20–35. http://dx.doi.org/10.1109/4434.656777.

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33

Lim, Sukhyun, and Byeong-Seok Shin. "A distance template for octree traversal in CPU-based volume ray casting." Visual Computer 24, no. 4 (2008): 229–37. http://dx.doi.org/10.1007/s00371-007-0203-y.

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34

Lim, Sukhyun, Daesung Lee, and Byeong-Seok Shin. "An image division approach for volume ray casting in multi-threading environment." Multimedia Tools and Applications 68, no. 2 (2011): 211–23. http://dx.doi.org/10.1007/s11042-011-0879-x.

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35

Mohanty, Manoranjan, Wei Tsang Ooi, and Pradeep K. Atrey. "Secret sharing approach for securing cloud-based pre-classification volume ray-casting." Multimedia Tools and Applications 75, no. 11 (2015): 6207–35. http://dx.doi.org/10.1007/s11042-015-2567-8.

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36

Lin, Lili, Shengyong Chen, Yan Shao, and Zichun Gu. "Plane-Based Sampling for Ray Casting Algorithm in Sequential Medical Images." Computational and Mathematical Methods in Medicine 2013 (2013): 1–5. http://dx.doi.org/10.1155/2013/874517.

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This paper proposes a plane-based sampling method to improve the traditional Ray Casting Algorithm (RCA) for the fast reconstruction of a three-dimensional biomedical model from sequential images. In the novel method, the optical properties of all sampling points depend on the intersection points when a ray travels through an equidistant parallel plan cluster of the volume dataset. The results show that the method improves the rendering speed at over three times compared with the conventional algorithm and the image quality is well guaranteed.

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37

Tian, Yuan, Xuefan Wang, Huang Yao, Jia Chen, Zhifeng Wang, and Liu Yi. "Occlusion handling using moving volume and ray casting techniques for augmented reality systems." Multimedia Tools and Applications 77, no. 13 (2017): 16561–78. http://dx.doi.org/10.1007/s11042-017-5228-2.

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38

HISHIDA, Hiroyuki, Takashi MICHIKAWA, Hiromasa SUZUKI, and Yutaka OHTAKE. "A Method for Calculating Volume for Casting Defects Using X Ray CT Data." Journal of the Japan Society for Precision Engineering 76, no. 8 (2010): 960–65. http://dx.doi.org/10.2493/jjspe.76.960.

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39

CHEN, Wei. "View Dependent Layer Sampling: An Approach to Hardware Implementation of Volume Ray Casting." Journal of Software 17, no. 3 (2006): 587. http://dx.doi.org/10.1360/jos170587.

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40

Semwal, Sudhanshu K., and Brian K. Barnhart. "Ray casting and the enclosing-net algorithm for extracting shapes from volume data." Computers in Biology and Medicine 25, no. 2 (1995): 261–76. http://dx.doi.org/10.1016/0010-4825(94)00044-q.

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41

Kwon, Koojoo, Supyeong Chae, and Byeong-Seok Shin. "Anti-aliasing on deformed area using adaptive super sampling during volume ray-casting." Biomedical Engineering Letters 1, no. 3 (2011): 168–73. http://dx.doi.org/10.1007/s13534-011-0027-6.

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42

Kosarina, E. I., A. A. Demidov, A. V. Smirnov, and P. V. Suvorov. "Digital reference images when evaluating the quality of castings from aluminum and magnesium alloys." Voprosy Materialovedeniya, no. 2(106) (August 1, 2021): 182–94. http://dx.doi.org/10.22349/1994-6716-2021-106-2-182-194.

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Reference X-ray images of defects in castings and welded joints have been used for many years in X-ray radiation inspection. With the transition to digital technologies, and the use of flat-panel detectors instead of radiographic film, the problem arose of creating reference digital images. Comparison of the digital image of the reference sample with the digital image of the test object can be carried out using software, which completely or partially excludes the subjective assessment of the operator, makes it possible to view doubtful areas of the image with magnification and without loss of

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43

Younkin, James E., Danairis Hernandez Morales, Jiajian Shen, et al. "Clinical Validation of a Ray-Casting Analytical Dose Engine for Spot Scanning Proton Delivery Systems." Technology in Cancer Research & Treatment 18 (January 1, 2019): 153303381988718. http://dx.doi.org/10.1177/1533033819887182.

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Purpose: To describe and validate the dose calculation algorithm of an independent second-dose check software for spot scanning proton delivery systems with full width at half maximum between 5 and 14 mm and with a negligible spray component. Methods: The analytical dose engine of our independent second-dose check software employs an altered pencil beam algorithm with 3 lateral Gaussian components. It was commissioned using Geant4 and validated by comparison to point dose measurements at several depths within spread-out Bragg peaks of varying ranges, modulations, and field sizes. Water equival

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44

LEE, JONG KWAN, and TIMOTHY S. NEWMAN. "EXPLORING GPU- AND CLUSTER-BASED IMPROVEMENTS FOR OVER-SAMPLED VOLUME RAY CASTING OPACITY CORRECTION." International Journal of Image and Graphics 12, no. 04 (2012): 1250025. http://dx.doi.org/10.1142/s0219467812500258.

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Performance improvements to the known opacity correction mechanisms for over-sampled volume ray casting (VRC), especially using two forms of commodity hardware, are explored. Data-parallel strategies that enable exploitation of parallelism using either: (1) a programmable graphics processing unit (GPU) or (2) cluster computation are a prime focus. The GPU-based approach is finely granular. The cluster-based approaches here utilize less finely granular processing that allows acceleration through multi-processing and multi-threading. These approaches also include features, such as early ray term

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45

Wu, Wei Jiang, Li Zhi Qin, Shu Ma, and Guo He Li. "Volume Rendering of 3D Borehole Data Based on GPU." Advanced Materials Research 765-767 (September 2013): 585–90. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.585.

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Taking 3D borehole data for research object, an algorithm flow of volume rendering based GPU is given. According to the limited and discrete characteristics of 3D borehole data, Kriging interpolation algorithm is used to construct a regular grid data model. Ray-casting algorithm based on GPU is realized with the Visualization Toolkit (VTK). The results show that after the application of volume rendering technology, it is easy to practice the functions of arbitrary section displaying, volume clipping and volume data extracting which are practicalities.

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46

HISHIDA, Hiroyuki, Takashi MICHIKAWA, Hiromasa SUZUKI, and Yutaka OHTAKE. "2219 A method for calculating volume for casting defects using X ray CT data." Proceedings of Design & Systems Conference 2009.19 (2009): 414–19. http://dx.doi.org/10.1299/jsmedsd.2009.19.414.

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47

Gu, Gibeom, and Duksu Kim. "Accurate and efficient GPU ray‐casting algorithm for volume rendering of unstructured grid data." ETRI Journal 42, no. 4 (2020): 608–18. http://dx.doi.org/10.4218/etrij.2019-0185.

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48

ZHOU, JIANLONG, ZHIYAN WANG, and KLAUS D. TÖNNIES. "FOCAL REGION-BASED VOLUME RENDERING." International Journal of Pattern Recognition and Artificial Intelligence 20, no. 05 (2006): 665–77. http://dx.doi.org/10.1142/s0218001406004909.

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In this paper, a new approach named focal region-based volume rendering for visualizing internal structures of volumetric data is presented. This approach presents volumetric information through integrating context information as the structure analysis of the data set with a lens-like focal region rendering to show more detailed information. This feature-based approach contains three main components: (i) A feature extraction model using 3D image processing techniques to explore the structure of objects to provide contextual information; (ii) An efficient ray-bounded volume ray casting renderin

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49

Lee, Byungsuk, Larry Di Girolamo, Guangyu Zhao, and Yizhe Zhan. "Three-Dimensional Cloud Volume Reconstruction from the Multi-angle Imaging SpectroRadiometer." Remote Sensing 10, no. 11 (2018): 1858. http://dx.doi.org/10.3390/rs10111858.

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Characterizing 3-D structure of clouds is needed for a more complete understanding of the Earth’s radiative and latent heat fluxes. Here we develop and explore a ray casting algorithm applied to data from the Multi-angle Imaging SpectroRadiometer (MISR) onboard the Terra satellite, in order to reconstruct 3-D cloud volumes of observed clouds. The ray casting algorithm is first applied to geometrically simple synthetic clouds to show that, under the assumption of perfect, clear-conservative cloud masks, the reconstruction method yields overestimation in the volume whose magnitude depends on the

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50

Zhang, Jin Shan, Yong Jun Xue, You Jun Guo, Chun Xiang Xu, and Wei Liang. "Effect of Si on As-Cast Microstructure in Quasicrystalline Al-Cu -Fe Alloy." Materials Science Forum 546-549 (May 2007): 619–22. http://dx.doi.org/10.4028/www.scientific.net/msf.546-549.619.

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Effect of Si on the forming ability of quasicrystalline phase in Al65Cu20Fe15 alloys fabricated under conventional casting conditions has been studied using X-ray diffraction (XRD), optical microscopy (OM), and scanning electron microscopy (SEM). The results show that under the conventional casting conditions, it is found that the addition of certain amount of Si into the Al-Cu-Fe melts can change the formation of Al62.5Cu25Fe12.5 quasicrystals during the solidification process. Compared with Al65Cu20Fe15 alloy, Al64.5Cu20Fe15Si0.5 alloy has smaller volume fraction of β phase solidifying initi

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