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Acceleration techniques for cubic interpolation MIP volume rendering

Published: 01 June 2021 Publication History

Abstract

Maximum intensity projection (MIP) is a volume visualization technique that is important in modern medical imaging systems. We propose a method to accelerate high-quality MIP volume rendering using cubic interpolation. First, our method skips more regions of volume data that do not affect the output image. To do this, we propose a method of transforming the B-spline interpolation function into a sub-division of Bezier spline interpolation. We generate the B-spline interpolation control points then the Bezier interpolation control points from three dimensional voxel values. The maximum value of each block is approximated using the Bezier interpolation control points due to the convex hull property of the Bezier spline. By accurately approximating the maximum value of each block, we can skip more unnecessary blocks. Second, we propose an efficient method of parallelization when performing volume visualization using a GPU. In order to reduce the number of memory transfers, our method determines the working shape of a warp, a bundle of 32 GPU threads, depending on the viewing direction. As a result, our method achieves a remarkable rendering speed improvement with no loss of image quality compared to previous studies, and performs high-quality MIP volume rendering using cubic interpolation at interactive speed.

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  • (2023)Optimization Techniques for GPU ProgrammingACM Computing Surveys10.1145/357063855:11(1-81)Online publication date: 16-Mar-2023

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Published In

cover image Multimedia Tools and Applications
Multimedia Tools and Applications  Volume 80, Issue 14
Jun 2021
1553 pages

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 June 2021
Accepted: 04 February 2021
Revision received: 08 December 2020
Received: 18 February 2020

Author Tags

  1. Volume rendering
  2. Cubic interpolation
  3. Bezier spline
  4. GPU memory divergence
  5. Maximum intensity projection

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  • (2023)Optimization Techniques for GPU ProgrammingACM Computing Surveys10.1145/357063855:11(1-81)Online publication date: 16-Mar-2023

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