Hardware-Based Nonlinear Filtering and Segmentation using High-Level Shading Languages.

Information

• Publication Type: Conference Paper
• Workgroup(s)/Project(s):
  • ADAPT: Advanced Diagnosis, Analysis and Planning Tools (in Medicine)
• Date: October 2003
• ISBN: 0780381203
• Publisher: IEEE
• Editor: G. Turk, J. van Wijk, K. Moorhead
• Booktitle: Proceedings of IEEE Visualization 2003
• Pages: 309 – 316
• Keywords: Hardware Acceleration, Segmentation, Non-linear Filtering

Abstract

Non-linear filtering is an important task for volume analysis. This paper presents hardware-based implementations of various nonlinear filters for volume smoothing with edge preservation. The Cg high-level shading language is used in combination with latest PC consumer graphics hardware. Filtering is divided into pervertex and per-fragment stages. In both stages we propose techniques to increase the filtering performance. The vertex program pre-computes texture coordinates in order to address all contributing input samples of the operator mask. Thus additional computations are avoided in the fragment program. The presented fragment programs preserve cache coherence, exploit 4D vector arithmetic, and internal fixed point arithmetic to increase performance. We show the applicability of non-linear filters as part of a GPU-based segmentation pipeline. The resulting binary mask is compressed and decompressed in the graphics memory on-the-fly.

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BibTeX

@inproceedings{Viola-2003-Har,
  title =      "Hardware-Based Nonlinear Filtering and Segmentation using
               High-Level Shading Languages.",
  author =     "Ivan Viola and Armin Kanitsar and Eduard Gr\"{o}ller",
  year =       "2003",
  abstract =   "Non-linear filtering is an important task for volume
               analysis. This paper presents hardware-based implementations
               of various nonlinear filters for volume smoothing with edge
               preservation. The Cg high-level shading language is used in
               combination with latest PC consumer graphics hardware.
               Filtering is divided into pervertex and per-fragment stages.
               In both stages we propose techniques to increase the
               filtering performance. The vertex program pre-computes
               texture coordinates in order to address all contributing
               input samples of the operator mask. Thus additional
               computations are avoided in the fragment program. The
               presented fragment programs preserve cache coherence,
               exploit 4D vector arithmetic, and internal fixed point
               arithmetic to increase performance. We show the
               applicability of non-linear filters as part of a GPU-based
               segmentation pipeline. The resulting binary mask is
               compressed and decompressed in the graphics memory
               on-the-fly.",
  month =      oct,
  isbn =       "0780381203",
  publisher =  "IEEE",
  editor =     "G. Turk, J. van Wijk, K. Moorhead",
  booktitle =  "Proceedings of IEEE Visualization 2003",
  pages =      "309--316",
  keywords =   "Hardware Acceleration, Segmentation, Non-linear Filtering",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2003/Viola-2003-Har/",
}