Current techniques for direct volume visualization offer only the ability to examine scalar fields. However most scientific explorations require the examination of vector and possibly tensor fields as well as numerous scalar fields. This paper describes an algorithm to directly render three-dimensional scalar and vector fields. The algorithm uses a combination of sampling and splatting techniques, that are extended to integrate display of vector field data within the image.
{"title":"Direct volume visualization of three-dimensional vector fields","authors":"R. Crawfis, N. Max","doi":"10.1145/147130.147150","DOIUrl":"https://doi.org/10.1145/147130.147150","url":null,"abstract":"Current techniques for direct volume visualization offer only the ability to examine scalar fields. However most scientific explorations require the examination of vector and possibly tensor fields as well as numerous scalar fields. This paper describes an algorithm to directly render three-dimensional scalar and vector fields. The algorithm uses a combination of sampling and splatting techniques, that are extended to integrate display of vector field data within the image.","PeriodicalId":20479,"journal":{"name":"Proceedings of the 1992 workshop on Volume visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78183193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Volume rendering techniques typically process volumetric data in raw, uncompressed form. As algorithmic and architectural advances improve rendering speeds, however, larger data sets will be evaluated requiring consideration of data storage and transmission issues. In this paper, we analyze the data compression requirements for volume rendering applications and present a solution based on vector quantization. The proposed system compresses volumetric data and then renders images directly from the new data format. Tests on a fluid flow data set demonstrate that good image quality may be achieved at a compression ratio of 17:1 with only a 5 percent cost in additional rendering time.
{"title":"Vector quantization for volume rendering","authors":"P. Ning, L. Hesselink","doi":"10.1145/147130.147152","DOIUrl":"https://doi.org/10.1145/147130.147152","url":null,"abstract":"Volume rendering techniques typically process volumetric data in raw, uncompressed form. As algorithmic and architectural advances improve rendering speeds, however, larger data sets will be evaluated requiring consideration of data storage and transmission issues. In this paper, we analyze the data compression requirements for volume rendering applications and present a solution based on vector quantization. The proposed system compresses volumetric data and then renders images directly from the new data format. Tests on a fluid flow data set demonstrate that good image quality may be achieved at a compression ratio of 17:1 with only a 5 percent cost in additional rendering time.","PeriodicalId":20479,"journal":{"name":"Proceedings of the 1992 workshop on Volume visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79170131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Volume rendering is a useful visualization technique for understanding the large amounts of data generated in a variety of scientific disciplines. Routine use of this technique is currently limited by its computational expense. We have designed a parallel volume rendering algorithm for MIMD architectures based on ray tracing and a novel task queue image partitioning technique. The combination of ray tracing and MIMD architectures allows us to employ algorithmic optimizations such as hierarchical opacity enumeration, early ray termination, and adaptive image sampling. The use of task queue image partitioning makes these optimizations efficient in a parallel framework. We have implemented our algorithm on the Stanford DASH Multiprocessor, a scalable shared-memory MIMD machine. Its single address-space and coherent caches provide programming ease and good performance for our algorithm. With only a few days of programming effort, we have obtained nearly linear speedups and near real-time frame update rates on a 48 processor machine. Since DASH is constructed from Silicon Graphics multiprocessors, our code runs on any Silicon Graphics workstation without modification.
{"title":"Volume rendering on scalable shared-memory MIMD architectures","authors":"Jason Nieh, M. Levoy","doi":"10.1145/147130.147141","DOIUrl":"https://doi.org/10.1145/147130.147141","url":null,"abstract":"Volume rendering is a useful visualization technique for understanding the large amounts of data generated in a variety of scientific disciplines. Routine use of this technique is currently limited by its computational expense. We have designed a parallel volume rendering algorithm for MIMD architectures based on ray tracing and a novel task queue image partitioning technique. The combination of ray tracing and MIMD architectures allows us to employ algorithmic optimizations such as hierarchical opacity enumeration, early ray termination, and adaptive image sampling. The use of task queue image partitioning makes these optimizations efficient in a parallel framework. We have implemented our algorithm on the Stanford DASH Multiprocessor, a scalable shared-memory MIMD machine. Its single address-space and coherent caches provide programming ease and good performance for our algorithm. With only a few days of programming effort, we have obtained nearly linear speedups and near real-time frame update rates on a 48 processor machine. Since DASH is constructed from Silicon Graphics multiprocessors, our code runs on any Silicon Graphics workstation without modification.","PeriodicalId":20479,"journal":{"name":"Proceedings of the 1992 workshop on Volume visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73576101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We examine various simple algorithms that exploit homogeneity and accumulate2 opacity for tracing rays through shaded volumes. Most of these methods have error criteria which allow them to trade quality for speed. The time vs. quality tradeoff for these adaptive methods is compared to fixed step multiresolution methods. These methods are also useful for general light transport in volumes.
{"title":"Fast algorithms for volume ray tracing","authors":"J. Danskin, P. Hanrahan","doi":"10.1145/147130.147155","DOIUrl":"https://doi.org/10.1145/147130.147155","url":null,"abstract":"We examine various simple algorithms that exploit homogeneity and accumulate2 opacity for tracing rays through shaded volumes. Most of these methods have error criteria which allow them to trade quality for speed. The time vs. quality tradeoff for these adaptive methods is compared to fixed step multiresolution methods. These methods are also useful for general light transport in volumes.","PeriodicalId":20479,"journal":{"name":"Proceedings of the 1992 workshop on Volume visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73760143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A technique to visualize S-dimensional flow fields int,eractively is described. The approach seems to represent the motion of the flow better than stat,ic images, and the motion is realtime even on low-t.o-medium range graphics workstations. It is part.icularly appropriat,e for compressible fluid flows, as several features of such flows are represent.ed simultaneously: velocity, density, and energy. The met~hocl works on warped grids, which are common in comput.a.t.io~lal fluid dynamics simulations. The method may be appropriate for other visualization applications involving a combinat.ion of scalar and vector qualit.ies. To achieve interactive speeds for motion representation, two usually unrelated hardware capabilities are utilized: color interpolat,ion and discrete
{"title":"Interactive visualization of flow fields","authors":"A. V. Gelder, J. Wilhelms","doi":"10.1145/147130.147149","DOIUrl":"https://doi.org/10.1145/147130.147149","url":null,"abstract":"A technique to visualize S-dimensional flow fields int,eractively is described. The approach seems to represent the motion of the flow better than stat,ic images, and the motion is realtime even on low-t.o-medium range graphics workstations. It is part.icularly appropriat,e for compressible fluid flows, as several features of such flows are represent.ed simultaneously: velocity, density, and energy. The met~hocl works on warped grids, which are common in comput.a.t.io~lal fluid dynamics simulations. The method may be appropriate for other visualization applications involving a combinat.ion of scalar and vector qualit.ies. To achieve interactive speeds for motion representation, two usually unrelated hardware capabilities are utilized: color interpolat,ion and discrete","PeriodicalId":20479,"journal":{"name":"Proceedings of the 1992 workshop on Volume visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84212432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A simple, but accurate, formal volume density optical model is developed for volume rendering scattered data or scalar fields from the finite element method, as opposed to scanned data sets where material classification is involved. The model is suitable either for ray tracing or projection methods and allows maximum flexibility in setting color and opacity. An expression is derived for the light intensity along a ray in terms of six userspecified transfer functions, three for optical density and three for color. Closed form solutions under several different assumptions are presented including a new exact result for the case that the transfer functions vary piecewise linearly along a ray segment within a cell.
{"title":"A volume density optical model","authors":"Peter L. Williams, N. Max","doi":"10.1145/147130.147151","DOIUrl":"https://doi.org/10.1145/147130.147151","url":null,"abstract":"A simple, but accurate, formal volume density optical model is developed for volume rendering scattered data or scalar fields from the finite element method, as opposed to scanned data sets where material classification is involved. The model is suitable either for ray tracing or projection methods and allows maximum flexibility in setting color and opacity. An expression is derived for the light intensity along a ray in terms of six userspecified transfer functions, three for optical density and three for color. Closed form solutions under several different assumptions are presented including a new exact result for the case that the transfer functions vary piecewise linearly along a ray segment within a cell.","PeriodicalId":20479,"journal":{"name":"Proceedings of the 1992 workshop on Volume visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79880515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work presents the implementation of data-parallel perspective volume rendering on a massively parallel SIMD computer, the MasPar MP-1, and shows the benefits of e$icient indirect addressing (an MP-1 feature) which allows individual processing elements to address their local memory independently. Emphasis is put on the geometric transformations required for volume rendering algorithms. TJte data-parallel algorithm separates multi-dimensional spatial transformations into a series of one-dimensional operations that can be performed in parallel on regular data domains, providing performance linear with data size. The rotation andperspective transformation is reduced to four shearlscale passes. The separable approach allows for predictable and regular data handling, independent of data values, allowing optimization of communication between processing elements. The communications required are data axis transpositions, wJtich can be peflormed using the MP-1 ‘s global router, which delivers scalable peflormance. Wrtualization allows graceful scaling in both problem size and architecture size, and a hierarchical design provides a flexible and portable fiamework suitable for different data-parallel SIMD architectures. 1 IMAGE-BASED VISUALIZATION Massively data-parallel architectures can realise close to peak performance on regularly structured image processing and viewing operations, allowing in some cases for real-time (or near real-time) interaction with modelling and viewing parameters [17]. A number of special architectures have been used for volume rendering [ 111. Polygon-based graphic algorithms pose problems of scalability, discretization independent of problem domain, and dependence on special purpose hardware for high performance [9]. Imageor pixel-based algorithms can be scalable with problem size, need not introduce geometrical artifacts and can be implemented on general purpose data-parallel computers. As a result, increases in model complexity (e.g. molecular modelling), empirical data generated from sensors (e.g. remote sensing and medical imaging) and inter* GPO Box 664, Canberra, ACT 2601, Australia Tel.: +616 275 0911 Fax: +616 257 1052 guy.vezina@csis.dit.csiro.au peter.fletcher@csis.dit.csiro.au phil.robertson@csis.dit.csiro.au Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. 1992 Workshop on Volume Visualization/l 0/92/Boston, MA o 1992 ACM 0-89791-5293/92/0010/00003...$1.50 action impose requirements that polygon-based systems often cannot satisfy. Image-based approaches are particularly well-suited to handling large multidimensional empirical data and the integration of compu
{"title":"Volume rendering on the MasPar MP-1","authors":"G. Vezina, P. Fletcher, P. K. Robertson","doi":"10.1145/147130.147138","DOIUrl":"https://doi.org/10.1145/147130.147138","url":null,"abstract":"This work presents the implementation of data-parallel perspective volume rendering on a massively parallel SIMD computer, the MasPar MP-1, and shows the benefits of e$icient indirect addressing (an MP-1 feature) which allows individual processing elements to address their local memory independently. Emphasis is put on the geometric transformations required for volume rendering algorithms. TJte data-parallel algorithm separates multi-dimensional spatial transformations into a series of one-dimensional operations that can be performed in parallel on regular data domains, providing performance linear with data size. The rotation andperspective transformation is reduced to four shearlscale passes. The separable approach allows for predictable and regular data handling, independent of data values, allowing optimization of communication between processing elements. The communications required are data axis transpositions, wJtich can be peflormed using the MP-1 ‘s global router, which delivers scalable peflormance. Wrtualization allows graceful scaling in both problem size and architecture size, and a hierarchical design provides a flexible and portable fiamework suitable for different data-parallel SIMD architectures. 1 IMAGE-BASED VISUALIZATION Massively data-parallel architectures can realise close to peak performance on regularly structured image processing and viewing operations, allowing in some cases for real-time (or near real-time) interaction with modelling and viewing parameters [17]. A number of special architectures have been used for volume rendering [ 111. Polygon-based graphic algorithms pose problems of scalability, discretization independent of problem domain, and dependence on special purpose hardware for high performance [9]. Imageor pixel-based algorithms can be scalable with problem size, need not introduce geometrical artifacts and can be implemented on general purpose data-parallel computers. As a result, increases in model complexity (e.g. molecular modelling), empirical data generated from sensors (e.g. remote sensing and medical imaging) and inter* GPO Box 664, Canberra, ACT 2601, Australia Tel.: +616 275 0911 Fax: +616 257 1052 guy.vezina@csis.dit.csiro.au peter.fletcher@csis.dit.csiro.au phil.robertson@csis.dit.csiro.au Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. 1992 Workshop on Volume Visualization/l 0/92/Boston, MA o 1992 ACM 0-89791-5293/92/0010/00003...$1.50 action impose requirements that polygon-based systems often cannot satisfy. Image-based approaches are particularly well-suited to handling large multidimensional empirical data and the integration of compu","PeriodicalId":20479,"journal":{"name":"Proceedings of the 1992 workshop on Volume visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85086868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Vandermeulen, P. Plets, Steven Ramkers, P. Suetens, G. Marchal
In this presentation, we discuss methods for an integrated display of cerebral blood vessels and brain structures using 3-D CT, MRI and MR Angiography images. We present methods for a three-dimensional semi-automatic delineation of brain structures in tomographic image sequences. Non-linear morphologic filters are applied to the MRA images to selectively enhance the blood vessel signal while suppressing the surrounding tissue. The geometric registration between the different cross-sectional imaging modalities is performed by the use of stereotactic frames, by matching of interactively indicated anatomical markers and by matching of corresponding anatomical surfaces. An integrated visualization of blood vessels and brain structures is obtained by a hybrid volume rendering method combining a maximum intensity projection with a transparent gray level gradient method.
{"title":"Integrated visualization of brain anatomy and cerebral blood vessels","authors":"D. Vandermeulen, P. Plets, Steven Ramkers, P. Suetens, G. Marchal","doi":"10.1145/147130.147146","DOIUrl":"https://doi.org/10.1145/147130.147146","url":null,"abstract":"In this presentation, we discuss methods for an integrated display of cerebral blood vessels and brain structures using 3-D CT, MRI and MR Angiography images. We present methods for a three-dimensional semi-automatic delineation of brain structures in tomographic image sequences. Non-linear morphologic filters are applied to the MRA images to selectively enhance the blood vessel signal while suppressing the surrounding tissue. The geometric registration between the different cross-sectional imaging modalities is performed by the use of stereotactic frames, by matching of interactively indicated anatomical markers and by matching of corresponding anatomical surfaces. An integrated visualization of blood vessels and brain structures is obtained by a hybrid volume rendering method combining a maximum intensity projection with a transparent gray level gradient method.","PeriodicalId":20479,"journal":{"name":"Proceedings of the 1992 workshop on Volume visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80414572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The process of volume rendering is computationally intensive especially when high quality imaging is required. We present an approach to realistic volume rendering which is based on a distributed system with a workstation front-end for scene composition andprevisualization, and a supercomputer serving as the primary rendering engine. We report on a new, expedient method for extending arbitrary su$ace-based ray tracers to support realistic rendering of volumes. In aadition, we describe a method for supporting ray tracing of a volume manipulated by CSG operations. Finally, an eficient, forward projection algorithm which exploits the multiprocessor, vector-arithmetic capabilities of the CRAY Y-MP supercomputer is described.
{"title":"Supercomputer assisted brain visualization with an extended ray tracer","authors":"D. Stredney, R. Yagel, S. F. May, M. Torello","doi":"10.1145/147130.147144","DOIUrl":"https://doi.org/10.1145/147130.147144","url":null,"abstract":"The process of volume rendering is computationally intensive especially when high quality imaging is required. We present an approach to realistic volume rendering which is based on a distributed system with a workstation front-end for scene composition andprevisualization, and a supercomputer serving as the primary rendering engine. We report on a new, expedient method for extending arbitrary su$ace-based ray tracers to support realistic rendering of volumes. In aadition, we describe a method for supporting ray tracing of a volume manipulated by CSG operations. Finally, an eficient, forward projection algorithm which exploits the multiprocessor, vector-arithmetic capabilities of the CRAY Y-MP supercomputer is described.","PeriodicalId":20479,"journal":{"name":"Proceedings of the 1992 workshop on Volume visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81854048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proceedings of the 1992 workshop on Volume visualization","authors":"L. Gelberg, H. Levkowitz","doi":"10.1145/147130","DOIUrl":"https://doi.org/10.1145/147130","url":null,"abstract":"","PeriodicalId":20479,"journal":{"name":"Proceedings of the 1992 workshop on Volume visualization","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1992-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75861645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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