Biomedical Engineering Reference
In-Depth Information
Fig. 5.8
Proposal of semantic visualization with ontology integration, represented with an infor-
mation visualization view. This can be considered as another scale because information is presented
in a different kind of abstraction. Images courtesy of 3B's Research Group (histological images of
meniscus and cartilage micro-CT dataset), OsiriX Project (knee CT dataset) [
10
], and LBB-MHH
(gait motion analysis)
organize biomedical data into semantically connected pieces of information. Clear
examples of that are tools for visually exploring biological networks as VisANT
[
82
], which works with Gene Ontology [
83
]. The annotation of knowledge associ-
ated to the data, either ontology-driven or keyword-based, can provide a semantically
meaningful visualization and interaction (see Fig.
5.8
).
The use of ontology concepts and relations could provide means for a rapid
retrieval of interesting relations during the interaction with the system [
84
], for
instance, allowing direct transition between parts that have similar meaning or have
been stored in the same dataset, but their spatial position is different. In addition, the
presentation of the content could be enhanced by view setup according to the stored
user profile. This user profile knowledge would be based on analysis of ontology
user queries and usage patterns [
85
].
Representation of uncertainty
The representation of uncertainty and errors in 3D diagrams should have the same
importance as in normal 2D scientific diagrams [
41
] because it is crucial for under-
standing the correctness of the visualization. There are several sources of uncertainty
during the representation process: acquisition, model, transformation (i.e. rescaling,
rotating) and visualization. Among others, the following methods can be used to
present uncertainty: use of displacement glyphs, arrows or patterns, blurring (note
the use of human psycho-physical abilities), and the combination of isosurfaces and
