Visual Analytics for the Representation, Exploration and Analysis of High-Dimensional, Multi-Faceted Medical Data

Information

• Publication Type: Article in a Book
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: July 2019
• Booktitle: Biomedical Visualisation
• Chapter: 10
• DOI: https://doi.org/10.1007/978-3-030-14227-8_10
• Editor: Springer
• Note: https://www.springer.com/gp/book/9783030142261
• Publisher: Springer
• Volume: 2
• Pages: 137 – 162

Abstract

Medicine is among research fields with a significant impact on humans and their health. Already for decades, medicine has established a tight coupling with the visualization domain, proving the importance of developing visualization techniques, designed exclusively for this research discipline. However, medical data is steadily increasing in complexity with the appearance of heterogeneous, multi-modal, multiparametric, cohort or population, as well as uncertain data. To deal with this kind of complex data, the field of Visual Analytics has emerged. In this chapter, we discuss the many dimensions and facets of medical data. Based on this classification, we provide a general overview of state-of-the-art visualization systems and solutions dealing with highdimensional, multi-faceted data. Our particular focus will be on multimodal, multi-parametric data, on data from cohort or population studies and on uncertain data, especially with respect to Visual Analytics applications for the representation, exploration, and analysis of highdimensional, multi-faceted medical data.

Additional Files and Images

Weblinks

• link
• Entry in the publication database of TU-Wien
• DOI: https://doi.org/10.1007/978-3-030-14227-8_10

BibTeX

@incollection{raidou_2019_springer,
  title =      "Visual Analytics for the Representation, Exploration and
               Analysis of High-Dimensional, Multi-Faceted Medical Data",
  author =     "Renata Raidou",
  year =       "2019",
  abstract =   "Medicine is among research fields with a significant impact
               on humans and their health. Already for decades, medicine
               has established a tight coupling with the visualization
               domain, proving the importance of developing visualization
               techniques, designed exclusively for this research
               discipline. However, medical data is steadily increasing in
               complexity with the appearance of heterogeneous,
               multi-modal, multiparametric, cohort or population, as well
               as uncertain data. To deal with this kind of complex data,
               the field of Visual Analytics has emerged. In this chapter,
               we discuss the many dimensions and facets of medical data.
               Based on this classification, we provide a general overview
               of state-of-the-art visualization systems and solutions
               dealing with highdimensional, multi-faceted data. Our
               particular focus will be on multimodal, multi-parametric
               data, on data from cohort or population studies and on
               uncertain data, especially with respect to Visual Analytics
               applications for the representation, exploration, and
               analysis of highdimensional, multi-faceted medical data.",
  month =      jul,
  booktitle =  "Biomedical Visualisation",
  chapter =    "10",
  doi =        "https://doi.org/10.1007/978-3-030-14227-8_10",
  editor =     "Springer",
  note =       "https://www.springer.com/gp/book/9783030142261",
  publisher =  "Springer",
  volume =     "2",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2019/raidou_2019_springer/",
}