Renata Raidou
, Barbora Kozlikova, Johanna Beyer, Timo Ropinski, Issei Fujishiro
NII Shonan Meeting Report No. 167: Formalizing Biological and Medical Visualization
ISSN 2186-7437
Information
- Publication Type: Miscellaneous Publication
- Workgroup(s)/Project(s):
- Date: 2020
- Note: ISSN 2186-7437
- Open Access: yes
- Number: TR-193-02-2020-1
Abstract
Medicine and biology are among the most important research fields, having a significant impact on humans and their health. For decades, these fields have been highly dependent on visualization—establishing a tight coupling which is crucial for the development of visualization techniques, designed exclusively for the disciplines of medicine and biology. These visualization techniques can be generalized by the term Biological and Medical Visualization—for short,BioMedical Visualization. BioMedical Visualization is not only an enabler for medical diagnosis and treatment, but also an influential component of today’s life science research. Many BioMedical domains can now be studied at various scales and dimensions, with different imaging modalities and simulations, and for a variety of purposes. Accordingly, BioMedical Visualization has also innumerable contributions in industrial applications. However, despite its proven scientific maturity and societal value, BioMedical Visualization is often treated within Computer Science as a mere application subdomain of the broader field of Visualization.To enable BioMedical Visualization to further thrive, it is important to formalize its characteristics independently from the general field of Visualization.Also, several lessons learnt within the context of BioMedical Visualization may be applicable and extensible to other application domains or to the parent field of Visualization. Formalization has become particularly urgent, with the latest advances of BioMedical Visualization—in particular, with respect to dealing with Big Data Visualization, e.g., for the visualization of multi-scale, multi-modal,cohort, or computational biology data. Rapid changes and new opportunities in the field, also regarding the incorporation of Artificial Intelligence with“human-in-the-loop” concepts within the field of Visual Analytics, compel further this formalization. By enabling the BioMedical Visualization community to have intensive discussions on the systematization of current knowledge, we can adequately prepare ourselves for future prospects and challenges, while also contributing to the broader Visualization community. During this 4-day seminar, which was the 150th NII Shonan meeting to be organized, we brought together 25 visualization experts from diverse institutions,backgrounds and expertise to discuss, identify, formalize, and document the specifics of our field. This has been a great opportunity to cover a range of relevant and contemporary topics, and as a systematic effort towards establishing better fundaments for the field and towards determining novel future challenges.In the upcoming sections of this report, we summarize the content of invited talks and of the eight main topics that were discussed within the working groups during the seminar.Additional Files and Images
Weblinks
BibTeX
@misc{raidou_shonan167,
title = "NII Shonan Meeting Report No. 167: Formalizing Biological
and Medical Visualization",
author = "Renata Raidou and Barbora Kozlikova and Johanna Beyer and
Timo Ropinski and Issei Fujishiro",
year = "2020",
abstract = "Medicine and biology are among the most important research
fields, having a significant impact on humans and their
health. For decades, these fields have been highly
dependent on visualization—establishing a tight coupling
which is crucial for the development of visualization
techniques, designed exclusively for the disciplines of
medicine and biology. These visualization techniques can be
generalized by the term Biological and Medical
Visualization—for short,BioMedical Visualization.
BioMedical Visualization is not only an enabler for medical
diagnosis and treatment, but also an influential component
of today’s life science research. Many BioMedical domains
can now be studied at various scales and dimensions, with
different imaging modalities and simulations, and for a
variety of purposes. Accordingly, BioMedical Visualization
has also innumerable contributions in industrial
applications. However, despite its proven scientific
maturity and societal value, BioMedical Visualization is
often treated within Computer Science as a mere
application subdomain of the broader field of
Visualization.To enable BioMedical Visualization to
further thrive, it is important to formalize its
characteristics independently from the general field of
Visualization.Also, several lessons learnt within the
context of BioMedical Visualization may be applicable and
extensible to other application domains or to the parent
field of Visualization. Formalization has become
particularly urgent, with the latest advances of BioMedical
Visualization—in particular, with respect to dealing with
Big Data Visualization, e.g., for the visualization of
multi-scale, multi-modal,cohort, or computational biology
data. Rapid changes and new opportunities in the field,
also regarding the incorporation of Artificial
Intelligence with“human-in-the-loop” concepts within
the field of Visual Analytics, compel further this
formalization. By enabling the BioMedical Visualization
community to have intensive discussions on the
systematization of current knowledge, we can adequately
prepare ourselves for future prospects and challenges,
while also contributing to the broader Visualization
community. During this 4-day seminar, which was the 150th
NII Shonan meeting to be organized, we brought together 25
visualization experts from diverse institutions,backgrounds
and expertise to discuss, identify, formalize, and
document the specifics of our field. This has been a great
opportunity to cover a range of relevant and contemporary
topics, and as a systematic effort towards establishing
better fundaments for the field and towards determining
novel future challenges.In the upcoming sections of this
report, we summarize the content of invited talks and of the
eight main topics that were discussed within the working
groups during the seminar.",
month = feb,
note = "ISSN 2186-7437",
number = "TR-193-02-2020-1",
URL = "https://www.cg.tuwien.ac.at/research/publications/2020/raidou_shonan167/",
}