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Authors: Paul Klemm 1 ; Sylvia Glaßer 1 ; Kai Lawonn 1 ; Marko Rak 1 ; Henry Völzke 2 ; Katrin Hegenscheid 2 and Bernhard Preim 1

Affiliations: 1 University of Magdeburg, Germany ; 2 University of Greifswald, Germany

ISBN: 978-989-758-088-8

Keyword(s): Epidemiology, Interactive Visual Analysis, Classification, Multi-Modal Data.

Related Ontology Subjects/Areas/Topics: Abstract Data Visualization ; Computer Vision, Visualization and Computer Graphics ; Databases and Visualization, Visual Data Mining ; General Data Visualization ; Large Data Visualization ; Visual Data Analysis and Knowledge Discovery ; Visualization Applications

Abstract: Epidemiology aims to provide insight into disease causations. Hence, subject groups (cohorts) are analyzed to correlate the subjects’ varying lifestyles, their medical properties and diseases. Recently, these cohort studies comprise medical image data. We assess potential relations between image-derived variables of the lumbar spine with lower back pain in a cross-sectional study. Therefore, an Interactive Visual Analysis (IVA) framework was created and tested with 2,540 segmented lumbar spine data sets. The segmentation results are evaluated and quantified by employing shape-describing variables, such as spine canal curvature and torsion. We analyze mutual dependencies among shape-describing variables and non-image variables, e.g., pain indicators. Therefore, we automatically train a decision tree classifier for each non-image variable. We provide an IVA technique to compare classifiers with a decision tree quality plot. As a first result, we conclude that image-based variables are o nly sufficient to describe lifestyle factors within the data. A correlation between lumbar spine shape and lower back pain could not be found with the automatically trained classifiers. However, the presented approach is a valuable extension for the IVA of epidemiological data. Hence, relations between non-image variables were successfully detected and described. (More)

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Paper citation in several formats:
Klemm P., Glaßer S., Lawonn K., Rak M., Völzke H., Hegenscheid K. and Preim B. (2015). Interactive Visual Analysis of Lumbar Back Pain - What the Lumbar Spine Tells About Your Life.In Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015) ISBN 978-989-758-088-8, pages 85-92. DOI: 10.5220/0005235500850092

@conference{ivapp15,
author={Paul Klemm and Sylvia Glaßer and Kai Lawonn and Marko Rak and Henry Völzke and Katrin Hegenscheid and Bernhard Preim},
title={Interactive Visual Analysis of Lumbar Back Pain - What the Lumbar Spine Tells About Your Life},
booktitle={Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015)},
year={2015},
pages={85-92},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005235500850092},
isbn={978-989-758-088-8},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015)
TI - Interactive Visual Analysis of Lumbar Back Pain - What the Lumbar Spine Tells About Your Life
SN - 978-989-758-088-8
AU - Klemm P.
AU - Glaßer S.
AU - Lawonn K.
AU - Rak M.
AU - Völzke H.
AU - Hegenscheid K.
AU - Preim B.
PY - 2015
SP - 85
EP - 92
DO - 10.5220/0005235500850092

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