Visualization of Cohort Study Data

The essence of epidemiology is the analysis of relations between causes and consequences on the health of the people. What combination of influences leads to an increased risk of getting a particular disease? In order to be able to analyze these complex associations, it requires extensive data basis in the form of populations studies as the “Study of Health in Pomerania” (SHIP), which iterativly gathers data for a large group of subjects (a cohort). To grasp the complex connections of this data, tools and visualizations are needed which go beyond the traditional statistical approaches used by epidemiologists. Techniques which connect the various socio-demographic and medical parameters in an interactive framework are needed to amplify the hypothesis-driven analysis of the complex data sets.

Medical image processing and visualization gaining in importance in epidemiology, since full body MRI scans are part of the data acquisition of large studies such as the SHIP. In addition to the detection of pathologies, the epidemiologists interested in offering new statistical indicators, such as the extent of a given structure or distances between different tissue types.

We focussed initially on the shape variation analysis of the spine. In practical terms, to distinguish pathological shape variance of age-related phenomena. To allow fot that, the medical data sets had to be processed in a way that allows comparisons between different subjects. We want to extend this approach in the next step of the entire lumbar spine.

As long-term goal we strive for a system that uses techniques of information visualization on socio-demographic and medical parameters and connects them with shape variance visualization of relevant structures. Such a system season would not be an impor-tant tool for epidemiologists who have statistical analysis and image-based to a large extent separate from each other methodically.

In addition to the goals specified in the project proposal, we are also interested in a in-depth understanding of epidemiological workflows and reasoning and coupling information visualizations with statistical tools. We focus on spine-related diseases and an understanding of socio-demographic variables and results from image processing (spine centerline, shapes of individual vertebrae) on and potential correlations to the disease status.

Contact

Name Paul Klemm
Adress Otto-von-Guericke-Universität Magdeburg
Fakultät für Informatik / ISG, PSF 4120
39016 Magdeburg
Phone (+49-391) 67-5 2527
Fax (+49 391) 67-1 11 64

Images

Publications


Bernhard Preim, Paul Klemm, Helwig Hauser, Katrin Hegenscheid, Steffen Oeltze, Klaus Toennies, Henry Völzke
Visualization in Medicine in Life Sciences III, pp. 221-248, 2016
BIBTeX
@INBOOK{Preim_2015_Cohort,
chapter = {{Visualization in Medicine in Life Sciences III}},
pages = {221--248},
title = {{Visual Analytics of Image-Centric Cohort Studies in Epidemiology}},
publisher = {Springer Verlag},
year = {2016},
editor = {Lars Linsen and Bernd Hamann and Hans-Christian Hege},
author = {Bernhard Preim and Paul Klemm and Helwig Hauser and Katrin Hegenscheid
and Steffen Oeltze and Klaus Toennies and Henry Völzke},
owner = {klemm},
timestamp = {2015.01.19}
}
Klaus D. Tönnies, Oliver Gloger, Marko Rak, Charlotte Winkler, Paul Klemm, Bernhard Preim, Henry Völzke
it - Information Technology, 57, pp. 22-29, 2015
BIBTeX
@ARTICLE{toennies_2015_it,
author = {Klaus D. Tönnies and Oliver Gloger and Marko Rak and Charlotte Winkler
and Paul Klemm and Bernhard Preim and Henry Völzke},
title = {Image analysis in epidemiological applications},
journal = {it - Information Technology},
year = {2015},
volume = {57},
pages = {22--29},
number = {1},
doi = {10.1515/itit-2014-1071},
owner = {klemm},
timestamp = {2015.04.01},
url = {http://dx.doi.org/10.1515/itit-2014-1071}
}
Paul Klemm, Sylvia Glaßer, Kai Lawonn, Marko Rak, Henry Völzke, Katrin Hegenscheid, Bernhard Preim
Proc. of the 6th International Conference on Information Visualization Theory and Applications (IVAPP), pp. 85-92, 2015
BIBTeX
@INPROCEEDINGS{klemm_2015_ivapp,
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}},
booktitle = {{Proc. of the 6th International Conference on Information Visualization
Theory and Applications (IVAPP)}},
year = {2015},
pages = {85--92},
address = {Berlin},
month = {März},
owner = {klemm},
timestamp = {2015.01.19}
}
Paul Klemm, Kai Lawonn, Sylvia Glaßer, Uli Niemann, Katrin Hegenscheid, Henry V\ olzke, Bernhard Preim
IEEE Transactions on Visualization and Computer Graphics (TVCG), 22 (1), pp. 81-90, 2015
BIBTeX
Media
@ARTICLE{Klemm_2015_TVCG,
author = {Paul Klemm and Kai Lawonn and Sylvia Glaßer and Uli Niemann and Katrin
Hegenscheid and Henry V{\"o}lzke and Bernhard Preim},
title = {{3D Regression Heat Map Analysis of Population Study Data}},
journal = {{IEEE Transactions on Visualization and Computer Graphics (TVCG)}},
year = {2015},
volume = {22 (1)},
pages = {81--90},
number = {1},
owner = {klemm},
timestamp = {2015.08.10}
}
Paul Klemm: 3D Regression Heat Map
P. Angelelli, S. Oeltze, C. Turkay, J. Haasz, E. Hodneland, A. Lundervold, A. Lundervold, B. Preim, H. Hauser
IEEE Computer Graphics and Applications, 34(5), pp. 70-82, 2014
BIBTeX
@Article{Angelelli_2014_CGA,
author = {P. Angelelli and S. Oeltze and C. Turkay and J. Haasz and E. Hodneland and A. Lundervold and A. Lundervold and B. Preim and H. Hauser},
title = {{Interactive Visual Analysis of Heterogeneous Cohort Study Data}},
journal = {{IEEE Computer Graphics and Applications}},
year = {2014},
volume = {34(5)},
number = {5},
pages = {70--82},
issn = {0272-1716},
doi = {http://dx.doi.org/10.1109/MCG.2014.40},
owner = {schumann},
timestamp = {2014.04.23},
}
Paul Klemm, Lisa Frauenstein, David Perlich, Katrin Hegenscheid, Henry Völzke, Bernhard Preim
Bildverarbeitung für die Medizin (BVM), pp. 180-185, 2014
BIBTeX
@INPROCEEDINGS{Klemm_2014_BVM,
author = {Paul Klemm and Lisa Frauenstein and David Perlich and Katrin Hegenscheid
and Henry Völzke and Bernhard Preim},
title = {{Clustering Socio-demographic and Medical Attribute Data in Cohort
Studies}},
booktitle = {{Bildverarbeitung für die Medizin (BVM)}},
year = {2014},
pages = {180--185},
owner = {klemm},
timestamp = {2014.01.01}
}
Paul Klemm, Steffen Oeltze-Jafra, Kai Lawonn, Katrin Hegenscheid, Henry Völzke, Bernhard Preim
IEEE Transactions on Visualization and Computer Graphics (TVCG), , pp. 1673-1682, 2014
BIBTeX
@ARTICLE{Klemm_2014_tvcg,
author = {Paul Klemm and Steffen Oeltze-Jafra and Kai Lawonn and Katrin Hegenscheid
and Henry Völzke and Bernhard Preim},
title = {{Interactive Visual Analysis of Image-Centric Cohort Study Data}},
journal = {{IEEE Transactions on Visualization and Computer Graphics (TVCG)}},
year = {2014},
pages = {1673--1682},
owner = {schumann},
timestamp = {2014.08.06}
}
Paul Klemm, Kai Lawonn, Marko Rak, Bernhard Preim, Klaus Tönnies, Katrin Hegenscheid, Henry Völzke, Steffen Oeltze
VMV 2013 - Vision Modeling Visualization, pp. 121-128, 2013
BIBTeX
@INPROCEEDINGS{Klemm_2013_VMV,
author = {Paul Klemm and Kai Lawonn and Marko Rak and Bernhard Preim and Klaus
Tönnies and Katrin Hegenscheid and Henry Völzke and Steffen Oeltze},
title = {{Visualization and Analysis of Lumbar Spine Canal Variability in
Cohort Study Data}},
booktitle = {{VMV 2013 - Vision, Modeling, Visualization}},
year = {2013},
editor = {Michael Bronstein, Jean Favre, and Kai Hormann},
pages = {121--128},
address = {Lugano},
month = {11.-13. September}
}
Paul Klemm, Steffen Oeltze, Katrin Hegenscheid, Henry Völzke, Klaus D. Tönnies, Bernhard Preim
VMV 2012 - Vision Modeling and Visualization, pp. 221-222, 2012
BIBTeX
@INPROCEEDINGS{Klemm_2012_VMV,
author = {Paul Klemm and Steffen Oeltze and Katrin Hegenscheid and Henry Völzke
and Klaus D. Tönnies and Bernhard Preim},
title = {{Visualization and Exploration of Shape Variance for the Analysis
of Cohort Study Data}},
booktitle = {{VMV 2012 - Vision, Modeling and Visualization}},
year = {2012},
pages = {221--222},
owner = {schumann},
timestamp = {2012.11.08}
}