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PARALLEL 3D IMAGE SEGMENTATION BY GPU-AMENABLE LEVEL SET SOLUTION

Hagan, Aaron M.
http://rave.ohiolink.edu/etdc/view?acc_num=kent1242262556

Abstract Details

2009, MS, Kent State University, College of Arts and Sciences / Department of Computer Science.
This thesis proposes an inherent parallel scheme for image segmentation of large data sets using the GPU. The method originates from an extended Lattice Boltzmann Model (LBM), and provides a new numerical solution for solving the level set equation. As a local, explicit and parallel scheme, this method lends itself to several favorable features: (1) Very easy to implement with the core program only requiring a few lines of code; (2) Implicit computation of curvatures; (3) Flexible control of generating smooth segmentation results; (4) Strong amenability to parallel computing, especially on the low-cost, powerful graphics hardware (GPU). The parallel computational scheme is also well suited for cluster computing, leading to solution for segmenting very large data sets, which cannot be accommodated by a single machine. While large data sets are typically found in various applications, current level set segmentation algorithms cannot easily operate on such data. This method proposes a new tool adopting distributed computing for the visualization community. Several examples are shown performing segmentation on the GPU and GPU cluster with satisfying results and performance.
Ye Zhao, PhD (Advisor)
Paul A Farrell, PhD (Committee Member)
Arden Ruttan, PhD (Committee Member)
58 p.
Computer Science
3D Image Segmentation; Large Data Set; Level Set; Graphics Hardware; Cluster Computing; Lattice Boltzmann Method

Recommended Citations

Citations

  • Hagan, A. M. (2009). PARALLEL 3D IMAGE SEGMENTATION BY GPU-AMENABLE LEVEL SET SOLUTION [Master's thesis, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1242262556

    APA Style (7th edition)

  • Hagan, Aaron. PARALLEL 3D IMAGE SEGMENTATION BY GPU-AMENABLE LEVEL SET SOLUTION. 2009. Kent State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1242262556.

    MLA Style (8th edition)

  • Hagan, Aaron. "PARALLEL 3D IMAGE SEGMENTATION BY GPU-AMENABLE LEVEL SET SOLUTION." Master's thesis, Kent State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=kent1242262556

    Chicago Manual of Style (17th edition)

kent1242262556
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© 2009, all rights reserved.
This open access ETD is published by Kent State University and OhioLINK.