Lessons learnt from developing visual analytics applications
for adaptive prostate cancer radiotherapy

D 2020

Lessons learnt from developing visual analytics applications for adaptive prostate cancer radiotherapy

RAIDOU, Renata Georgia, Katarína FURMANOVÁ, Nicolas GROSSMANN, Oscar CASARES-MAGAZ, Vitali MOISEENKO et. al.

Basic information

Original name

Lessons learnt from developing visual analytics applications for adaptive prostate cancer radiotherapy

Authors

RAIDOU, Renata Georgia, Katarína FURMANOVÁ, Nicolas GROSSMANN, Oscar CASARES-MAGAZ, Vitali MOISEENKO, John P EINCK, Eduard GRÖLLER and Ludvig P MUREN

Edition

Norrköping, Sweden, VisGap - The Gap between Visualization Research and Visualization Software, p. 51-58, 8 pp. 2020

Publisher

The Eurographics Association

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

Sweden

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

URL

ISBN

978-3-03868-125-0

DOI

http://dx.doi.org/10.2312/visgap.20201110

Keywords in English

visual analytics; radiotherapy

Abstract

V originále

In radiotherapy (RT), changes in patient anatomy throughout the treatment period might lead to deviations between planned and delivered dose, resulting in inadequate tumor coverage and/or overradiation of healthy tissues. Adapting the treatment to account for anatomical changes is anticipated to enable higher precision and less toxicity to healthy tissues. Corresponding tools for the in-depth exploration and analysis of available clinical cohort data were not available before our work. In this paper, we discuss our on-going process of introducing visual analytics to the domain of adaptive RT for prostate cancer. This has been done through the design of three visual analytics applications, built for clinical researchers working on the deployment of robust RT treatment strategies. We focus on describing our iterative design process, and we discuss the lessons learnt from our fruitful collaboration with clinical domain experts and industry, interested in integrating our prototypes into their workflow.

Citovat

RAIDOU, Renata Georgia, Katarína FURMANOVÁ, Nicolas GROSSMANN, Oscar CASARES-MAGAZ, Vitali MOISEENKO, John P EINCK, Eduard GRÖLLER and Ludvig P MUREN. Lessons learnt from developing visual analytics applications for adaptive prostate cancer radiotherapy. Online. In Christina Gillmann, Michael Krone, Guido Reina, Thomas Wischgoll. VisGap - The Gap between Visualization Research and Visualization Software. Norrköping, Sweden: The Eurographics Association, 2020, p. 51-58. ISBN 978-3-03868-125-0. Available from: https://dx.doi.org/10.2312/visgap.20201110.

@inproceedings{1737817,
   author = {Raidou, Renata Georgia and Furmanová, Katarína and Grossmann, Nicolas and CasaresandMagaz, Oscar and Moiseenko, Vitali and Einck, John P and Gröller, Eduard and Muren, Ludvig P},
   address = {Norrköping, Sweden},
   booktitle = {VisGap - The Gap between Visualization Research and Visualization Software},
   doi = {http://dx.doi.org/10.2312/visgap.20201110},
   editor = {Christina Gillmann, Michael Krone, Guido Reina, Thomas Wischgoll},
   keywords = {visual analytics; radiotherapy},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Norrköping, Sweden},
   isbn = {978-3-03868-125-0},
   pages = {51-58},
   publisher = {The Eurographics Association},
   title = {Lessons learnt from developing visual analytics applications for adaptive prostate cancer radiotherapy},
   url = {https://diglib.eg.org/handle/10.2312/visgap20201110},
   year = {2020}
}

TY  - JOUR
ID  - 1737817
AU  - Raidou, Renata Georgia - Furmanová, Katarína - Grossmann, Nicolas - Casares-Magaz, Oscar - Moiseenko, Vitali - Einck, John P - Gröller, Eduard - Muren, Ludvig P
PY  - 2020
TI  - Lessons learnt from developing visual analytics applications for adaptive prostate cancer radiotherapy
PB  - The Eurographics Association
CY  - Norrköping, Sweden
SN  - 9783038681250
KW  - visual analytics
KW  - radiotherapy
UR  - https://diglib.eg.org/handle/10.2312/visgap20201110
N2  - In radiotherapy (RT), changes in patient anatomy throughout the treatment period might lead to deviations between planned and delivered dose, resulting in inadequate tumor coverage and/or overradiation of healthy tissues. Adapting the treatment to account for anatomical changes is anticipated to enable higher precision and less toxicity to healthy tissues. Corresponding tools for the in-depth exploration and analysis of available clinical cohort data were not available before our work. In this paper, we discuss our on-going process of introducing visual analytics to the domain of adaptive RT for prostate cancer. This has been done through the design of three visual analytics applications, built for clinical researchers working on the deployment of robust RT treatment strategies. We focus on describing our iterative design process, and we discuss the lessons learnt from our fruitful collaboration with clinical domain experts and industry, interested in integrating our prototypes into their workflow.
ER  -

RAIDOU, Renata Georgia, Katarína FURMANOVÁ, Nicolas GROSSMANN, Oscar CASARES-MAGAZ, Vitali MOISEENKO, John P EINCK, Eduard GRÖLLER and Ludvig P MUREN. Lessons learnt from developing visual analytics applications for adaptive prostate cancer radiotherapy. Online. In Christina Gillmann, Michael Krone, Guido Reina, Thomas Wischgoll. \textit{VisGap - The Gap between Visualization Research and Visualization Software}. Norrköping, Sweden: The Eurographics Association, 2020, p.~51-58. ISBN~978-3-03868-125-0. Available from: https://dx.doi.org/10.2312/visgap.20201110.

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