Denoising Medical Surface Meshes for 3D-Printing

Information

• Publication Type: Bachelor Thesis
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: 2015
• Date (Start): 1. April 2015
• Date (End): 30. November 2015
• Matrikelnummer: 1129406
• First Supervisor: Eduard Gröller
• Second Supervisor: Peter Mindek

Abstract

3D-printed anatomical models obtained from medical volume data (CT, MRI, ultrasound) can be used for surgery-planning, diagnosis, fabrication of implants and education. Surface meshes that are extracted from real-world data typically suffer from noise, as well as other types of artifacts. This thesis compares different common denoising algorithms and asseses their applicability to medical surface meshes, particularly with regard to subsequent 3D-printing. Additionally this thesis proposes an approach to detect and remove long, thin artifacts, which are commonly found in medical data. If they are removed before smoothing, deformations in the smoothed mesh can be prevented and less support structures are needed for 3D-printing.

Additional Files and Images

Weblinks

No further information available.

BibTeX

@bachelorsthesis{gostler-2015-3dp,
  title =      "Denoising Medical Surface Meshes for 3D-Printing",
  author =     "Anna Gostler",
  year =       "2015",
  abstract =   "3D-printed anatomical models obtained from medical volume
               data (CT, MRI, ultrasound) can be used for surgery-planning,
               diagnosis, fabrication of implants and education. Surface
               meshes that are extracted from real-world data typically
               suffer from noise, as well as other types of artifacts. This
               thesis compares different common denoising algorithms and
               asseses their applicability to medical surface meshes,
               particularly with regard to subsequent 3D-printing.
               Additionally this thesis proposes an approach to detect and
               remove long, thin artifacts, which are commonly found in
               medical data. If they are removed before smoothing,
               deformations in the smoothed mesh can be prevented and less
               support structures are needed for 3D-printing.",
  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/2015/gostler-2015-3dp/",
}