Real-Time Mono- and Multi-Volume Rendering of Large Medical Datasets on Standard PC Hardware

Information

• Publication Type: PhD-Thesis
• Workgroup(s)/Project(s): not specified
• Date: April 2005
• Date (Start): October 2002
• Date (End): April 2005
• First Supervisor: Eduard Gröller

Abstract

Direct Volume Visualization is an efficient technique to explore complex structures within volumetric data. Its main advantage, compared to standard 3D surface rendering, is the ability to perform semitransparent rendering in order to provide more information about spatial relationships of different structures. Semitransparent rendering requires to process a huge amount of data. The size of volumetric data is rapidly increasing, on the one hand due to the boost of processing power in the past years, and on the other hand due to improved capabilities of newer acquisition devices. This large data presents a challenge to current rendering architectures and techniques. The enormous data sizes introduce a growing demand for interactive 3D visualization. Conventional slicing methods already reach their limit of usability due to the enormous amount of slices. 3D visualization is more and more explored as an attractive alternative additional method for examinations of large medical data to support the necessary 2D examination. Within this dissertation a set of approaches to handle and render large volumetric data is developed, enabling significant performance improvements due to a much better utilization of the CPUs processing power and available memory bandwidth. At first, highly efficient approaches for addressing and processing of a cache efficient memory layout for volumetric data are presented. These approaches serve as a base for a full-blown high-quality raycasting system, capable of handling large data up to 3GB, a limitation imposed by the virtual address space of current consumer operating systems. The core acceleration techniques of this system are a refined caching scheme for gradient estimation in conjunction with a hybrid skipping and removal of transparent regions to reduce the amount of data to be processed. This system is extended so that efficient processing of multiple large data sets is possible. An acceleration technique for direct volume rendering of scenes, composed of multiple volumetric objects, is developed; it is based on the distinction between regions of intersection, which need costly multi-volume processing, and regions containing only one volumetric object, which can be efficiently processed. Furthermore, V-Objects, a concept of modeling scenes consisting of multiple volumetric objects, are presented. It is demonstrated that the concept of V-Objects in combination with direct volume rendering, is a promising technique for visualizing medical data and can provide advanced means to explore and investigate data. In the second part of the dissertation, an alternative to grid-based volume graphics is presented: Vots, a point-based representation of volumetric data. It is a novel primitive for volumetric data modeling, processing, and rendering. A new paradigm is presented by moving the data representation from a discrete representation to an implicit one.

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BibTeX

@phdthesis{Grimm-thesis,
  title =      "Real-Time Mono- and Multi-Volume Rendering of Large Medical
               Datasets on Standard PC Hardware",
  author =     "S\"{o}ren Grimm",
  year =       "2005",
  abstract =   "Direct Volume Visualization is an efficient technique to
               explore complex structures within volumetric data. Its main
               advantage, compared to standard 3D surface rendering, is the
               ability to perform semitransparent rendering in order to
               provide more information about spatial relationships of
               different structures. Semitransparent rendering requires to
               process a huge amount of data. The size of volumetric data
               is rapidly increasing, on the one hand due to the boost of
               processing power in the past years, and on the other hand
               due to improved capabilities of newer acquisition devices.
               This large data presents a challenge to current rendering
               architectures and techniques. The enormous data sizes
               introduce a growing demand for interactive 3D visualization.
               Conventional slicing methods already reach their limit of
               usability due to the enormous amount of slices. 3D
               visualization is more and more explored as an attractive
               alternative additional method for examinations of large
               medical data to support the necessary 2D examination. Within
               this dissertation a set of approaches to handle and render
               large volumetric data is developed, enabling significant
               performance improvements due to a much better utilization of
               the CPUs processing power and available memory bandwidth. At
               first, highly efficient approaches for addressing and
               processing of a cache efficient memory layout for volumetric
               data are presented. These approaches serve as a base for a
               full-blown high-quality raycasting system, capable of
               handling large data up to 3GB, a limitation imposed by the
               virtual address space of current consumer operating systems.
               The core acceleration techniques of this system are a
               refined caching scheme for gradient estimation in
               conjunction with a hybrid skipping and removal of
               transparent regions to reduce the amount of data to be
               processed. This system is extended so that efficient
               processing of multiple large data sets is possible. An
               acceleration technique for direct volume rendering of
               scenes, composed of multiple volumetric objects, is
               developed; it is based on the distinction between regions of
               intersection, which need costly multi-volume processing, and
               regions containing only one volumetric object, which can be
               efficiently processed. Furthermore, V-Objects, a concept of
               modeling scenes consisting of multiple volumetric objects,
               are presented. It is demonstrated that the concept of
               V-Objects in combination with direct volume rendering, is a
               promising technique for visualizing medical data and can
               provide advanced means to explore and investigate data. In
               the second part of the dissertation, an alternative to
               grid-based volume graphics is presented: Vots, a point-based
               representation of volumetric data. It is a novel primitive
               for volumetric data modeling, processing, and rendering. A
               new paradigm is presented by moving the data representation
               from a discrete representation to an implicit one.",
  month =      apr,
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2005/Grimm-thesis/",
}