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Clustered Grid Cell Data Structure for Isosurface Rendering
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
2020 (English)In: Journal of WSCG, ISSN 1213-6972, E-ISSN 1213-6964, Vol. 28, no 1-2, p. 9-17Article in journal (Refereed) Published
Abstract [en]

Active grid cells in scalar volume data are typically identified by many isosurface rendering methods when extracting another representation of the data for rendering. However, the use of grid cells themselves as rendering primitives is not extensively explored in the literature. In this paper, we propose a cluster-based data structure for storing the data of active grid cells for fast cell rasterisation via billboard splatting. Compared to previous cell rasterisation approaches, eight corner scalar values are stored with each active grid cell, so that the full volume data is not required during rendering. The grid cells can be quickly extracted and use about 37 percent memory compared to a typical efficient mesh-based representation, while supporting large grid sizes. We present further improvements such as a visibility buffer for cluster culling and EWA-based interpolation of attributes such as normals. We also show that our data structure can be used for hybrid ray tracing or path tracing to compute global illumination.

Place, publisher, year, edition, pages
2020. Vol. 28, no 1-2, p. 9-17
Keywords [en]
Point-based rendering, Visibility, Ray tracing
National Category
Computer Sciences
Research subject
Computerized Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-402896DOI: 10.24132/JWSCG.2020.28.2OAI: oai:DiVA.org:uu-402896DiVA, id: diva2:1387278
Conference
Virtual WSCG 2020 conference, May 19, Plzen, Czech Republic
Available from: 2020-01-21 Created: 2020-01-21 Last updated: 2021-06-02Bibliographically approved
In thesis
1. Modeling and Visualization for Virtual Interaction with Medical Image Data
Open this publication in new window or tab >>Modeling and Visualization for Virtual Interaction with Medical Image Data
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Interactive systems for exploring and analysing medical three dimensional (3D) volume image data using techniques such as stereoscopic rendering and haptics can lead to new workflows for virtual surgery planning. This includes the design of patient-specific surgical guides and plates for additive manufacturing (3D printing). Our applications, medical visualization and cranio-maxillofacial surgery planning, involve large volume data such as computed tomo\-graphy (CT) images with millions of data points. This motivates the development of fast and efficient methods for visualization and haptic rendering, as well as the development of efficient modeling techniques for simplifying the design of 3D printable parts. In this thesis, we develop methods for visualization and haptic rendering of isosurfaces in volume image data, and show applications of these methods to medical visualization and virtual surgery planning. We further develop methods for modeling surgical guides and plates for cranio-maxillofacial surgery, and integrate them into our system for haptics-assisted surgery planning called HASP. This system is now installed at the department of surgical sciences, Uppsala University, and is being evaluated for use in clinical research.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2020. p. 50
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1898
Keywords
medical image processing, volume rendering, haptic rendering, medical visualization, virtual surgery planning
National Category
Computer Sciences Medical Imaging
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-403104 (URN)978-91-513-0864-7 (ISBN)
Public defence
2020-03-13, ITC 2446, Lägerhyddsvägen 2, Hus 2, Polacksbacken, Uppsala, 10:15 (English)
Opponent
Supervisors
Available from: 2020-02-19 Created: 2020-01-23 Last updated: 2025-02-09

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Nysjö, Fredrik

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