Research on Graphical Interfaces to Perform Anatomical Queries on Large Collections of Gene Expression Images

Information

• Publication Type: Bachelor Thesis
• Workgroup(s)/Project(s):
  • Visualization Group
  • VRVis Competence Center
• Date: April 2018
• Date (Start): 6. October 2017
• Date (End): 6. April 2018
• Matrikelnummer: 1425123
• First Supervisor: Eduard Gröller

Abstract

As image information is increasing sharply, searching and presenting interesting images in large databases have become more and more important in image management. In this paper, an optimizing graphical query interface was designed for anatomical search to present more valuable information from the large neuro-anatomical image collections of Drosophila (fruit fly) brains. In order to achieve the goal, the relevant websites of “Fly Circuit”, “Fly Light” and “Allen Mouse Brain Atlas”, and the image management software of PivotViewer and Zegami were investigated firstly. Then, analysis and comparison for the mentioned tools using different perspectives were conducted to define the guidelines for best practices out of them. Based on the findings, several redesigns are proposed for neuro-anatomical query interfaces and part of them were implemented.

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BibTeX

@bachelorsthesis{Cai_2018,
  title =      "Research on Graphical Interfaces to Perform Anatomical
               Queries on Large Collections of Gene Expression Images",
  author =     "Yan Cai",
  year =       "2018",
  abstract =   "As image information is increasing sharply, searching and
               presenting interesting images in large databases have become
               more and more important in image management. In this paper,
               an optimizing graphical query interface was designed for
               anatomical search to present more valuable information from
               the large neuro-anatomical image collections of Drosophila
               (fruit fly) brains. In order to achieve the goal, the
               relevant websites of “Fly Circuit”, “Fly Light” and
               “Allen Mouse Brain Atlas”, and the image management
               software of PivotViewer and Zegami were investigated
               firstly. Then, analysis and comparison for the mentioned
               tools using different perspectives were conducted to define
               the guidelines for best practices out of them. Based on the
               findings, several redesigns are proposed for
               neuro-anatomical query interfaces and part of them were
               implemented. ",
  month =      apr,
  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/Cai_2018/",
}