Ten Open Challenges in Medical Visualization

Information

• Publication Type: Journal Paper (without talk)
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: October 2021
• DOI: 10.1109/MCG.2021.3094858
• Journal: IEEE Computer Graphics and Applications
• Number: 5
• Open Access: yes
• Volume: 41
• Pages: 7 – 15

Abstract

The medical domain has been an inspiring application area in visualization research for many years already, but many open challenges remain. The driving forces of medical visualization research have been strengthened by novel developments, for example, in deep learning, the advent of affordable VR technology, and the need to provide medical visualizations for broader audiences. At IEEE VIS 2020, we hosted an Application Spotlight session to highlight recent medical visualization research topics. With this article, we provide the visualization community with ten such open challenges, primarily focused on challenges related to the visualization of medical imaging data. We first describe the unique nature of medical data in terms of data preparation, access, and standardization. Subsequently, we cover open visualization research challenges related to uncertainty, multimodal and multiscale approaches, and evaluation. Finally, we emphasize challenges related to users focusing on explainable AI, immersive visualization, P4 medicine, and narrative visualization.

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• Entry in the publication database of TU-Wien
• DOI: 10.1109/MCG.2021.3094858

BibTeX

@article{Gillmann2021,
  title =      "Ten Open Challenges in Medical Visualization ",
  author =     "Christina Gillmann and Noeska Natasja Smit and Eduard
               Gr\"{o}ller and Bernhard Preim and Anna Vilanova i Bartroli
               and Thomas Wischgoll",
  year =       "2021",
  abstract =   "The medical domain has been an inspiring application area in
               visualization research for many years already, but many open
               challenges remain. The driving forces of medical
               visualization research have been strengthened by novel
               developments, for example, in deep learning, the advent of
               affordable VR technology, and the need to provide medical
               visualizations for broader audiences. At IEEE VIS 2020, we
               hosted an Application Spotlight session to highlight recent
               medical visualization research topics. With this article, we
               provide the visualization community with ten such open
               challenges, primarily focused on challenges related to the
               visualization of medical imaging data. We first describe the
               unique nature of medical data in terms of data preparation,
               access, and standardization. Subsequently, we cover open
               visualization research challenges related to uncertainty, 
               multimodal and multiscale approaches, and evaluation.
               Finally, we emphasize challenges related to users focusing
               on explainable AI, immersive visualization, P4 medicine, and
               narrative visualization. ",
  month =      oct,
  doi =        "10.1109/MCG.2021.3094858",
  journal =    "IEEE Computer Graphics and Applications",
  number =     "5",
  volume =     "41",
  pages =      "7--15",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2021/Gillmann2021/",
}