Transfer Function Widget for Tri-Modal Volume Exploration

Information

• Publication Type: Bachelor Thesis
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: November 2018
• Date (Start): 1. March 2018
• Date (End): 6. November 2018
• Matrikelnummer: 01429462
• First Supervisor: Eduard Gröller

Abstract

Volumetric visualization is an essential tool in medical studies and materials science, as it enables the analysis and exploration of the inner structure of objects. With the introduction of new equipment and techniques, the datasets become more complex, making it an increasingly common task in material analysis to handle three modalities at once. For instance, a single industrial computed-tomography scan of an object can output absorption contrast, differential phase contrast and dark-field contrast volumes (modalities). However, modern software is falling behind with these advancements, as they still do not provide dedicated tools for this use. This thesis aims to test the feasibility of a transfer function user interface for tri-modal datasets, with a focus on usability, taking into consideration the needs of material analysis experts. The development process (from the initial concepts to a software prototype) is described, and the resulting tool, developed as a module for open_iA (a visual analysis and volumetric processing application), is presented. It uses the standard 1D color-opacity transfer function for each modality together with a barycentric coordinates method to blend the three modalities together. For the modalities of an industrial computed-tomography dataset (absorption contrast, differential phase contrast and dark-field contrast), the tool can successfully accelerate and facilitate volume exploration.

Additional Files and Images

Weblinks

No further information available.

BibTeX

@bachelorsthesis{Melo_2018_11,
  title =      "Transfer Function Widget for Tri-Modal Volume Exploration",
  author =     "Lucas  da Cunha Melo",
  year =       "2018",
  abstract =   "Volumetric visualization is an essential tool in medical
               studies and materials science, as it enables the analysis
               and exploration of the inner structure of objects. With the
               introduction of new equipment and techniques, the datasets
               become more complex, making it an increasingly common task
               in material analysis to handle three modalities at once. For
               instance, a single industrial computed-tomography scan of an
               object can output absorption contrast, differential phase
               contrast and dark-field contrast volumes (modalities).
               However, modern software is falling behind with these
               advancements, as they still do not provide dedicated tools
               for this use. This thesis aims to test the feasibility of a
               transfer function user interface for tri-modal datasets,
               with a focus on usability, taking into consideration the
               needs of material analysis experts. The development process
               (from the initial concepts to a software prototype) is
               described, and the resulting tool, developed as a module for
               open_iA (a visual analysis and volumetric processing
               application), is presented. It uses the standard 1D
               color-opacity transfer function for each modality together
               with a barycentric coordinates method to blend the three
               modalities together. For the modalities of an industrial
               computed-tomography dataset (absorption contrast,
               differential phase contrast and dark-field contrast), the
               tool can successfully accelerate and facilitate volume
               exploration.",
  month =      nov,
  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/2018/Melo_2018_11/",
}