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@PHDTHESIS{Hnel:835868,
author = {Hänel, Claudia},
othercontributors = {Kuhlen, Torsten and Preim, Bernhard},
title = {{M}ethods for immersive visual analysis of structural brain
data},
school = {RWTH Aachen University},
type = {Dissertation},
address = {Aachen},
publisher = {RWTH Aachen University},
reportid = {RWTH-2021-10888},
pages = {1 Online-Ressource : Illustrationen, Diagramme},
year = {2021},
note = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
University 2022; Dissertation, RWTH Aachen University, 2021},
abstract = {The visual analysis of structural brain data is an
important method to understand the basics of anatomy,
relationships of structures, and functionality of the brain.
While the data are three-dimensional by their nature, many
visual analysis tools focus on two-dimensional
visualization. This thesis emphasizes the spatial aspect of
the data and presents methods for a valuable
three-dimensional visualization that can support
neuroscientists in their everyday work. In order to address
the heterogeneity of available structural brain data, three
categories are considered: small-scale brain atlas, time
series, and large-scale data. For these, this thesis
presents interactive methods for visual analysis processes.
In order to retain the spatial orientation, depth cues like
additional anatomical slices or superimposed brain
structures are considered one important aspect for the
three-dimensional visualization. Furthermore, a distinctive
significance of this thesis is the consideration of
Immersive Virtual Environments (IVEs) as a visualization
platform. In contrast to desktop environments, the spatial
perception is enhanced due to the natural three-dimensional
perception based on stereoscopic rendering and head
tracking. This simplifies the spatial orientation in the
data set and is found to be a beneficial, complementary
approach by cooperating neuroscientists. Accordingly, the
user interaction and experience with the presented visual
analysis tools are designed to be user-friendly in desktop
and immersive environments. Therefore, this thesis presents
two studies on optimizing the user experience for volume
rendering applications in IVEs, which find a trade-off
between visual quality and interactivity. The thesis
concludes with a prototype for provenance tracking in order
to go further beyond a pure visualization work and provide
an additional way to gain insight into the data.},
cin = {124620 / 120000},
ddc = {004},
cid = {$I:(DE-82)124620_20151124$ / $I:(DE-82)120000_20140620$},
typ = {PUB:(DE-HGF)11},
doi = {10.18154/RWTH-2021-10888},
url = {https://publications.rwth-aachen.de/record/835868},
}
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