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Buchbeiträge:

R. Raidou:
"Visual Analytics for the Representation, Exploration and Analysis of High-Dimensional, Multi-Faceted Medical Data";
in: "Biomedical Visualisation", 2; Springer International Publishing, 2019, ISBN: 978-3-030-14227-8, S. 137 - 162.



Kurzfassung englisch:
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.


Elektronische Version der Publikation:
https://www.springer.com/gp/book/9783030142261


Erstellt aus der Publikationsdatenbank der Technischen Universitšt Wien.