Abstract
A rising number of epidemiological studies apply imaging technologies. Images are not features themselves but provide raw data from which features are extracted. Different to other applications of analysis of medical images the data is analyzed statistically across the cohort. It results in unique requirements regarding the development of methods to efficiently integrate varying domain knowledge into the process without compromising comparability of results across subjects or time. Examples from two different strategies are presented and discussed.
About the authors
Klaus D. Toennies is professor for computer vision in the Department of Computer Science at the Otto-von-Guericke-University Magdeburg. He received his Ph.D. and M.Sc. in Computer Science from the Technische Universität Berlin in 1987 and 1983, respectively. After holding a PostDoc position at the University of Pennsylvania, he received a habilitation degree from the Technische Universität Berlin in 1993. His research interests are model-based image analysis and applications in medical image analysis.
Fakultät für Informatik, ISG, Otto-von-Guericke-Universität, Universitätsplatz 2, 39106 Magdeburg, Germany
Oliver Gloger is member of the Institute for Community Medicine at the Ernst-Moritz-Arndt University Greifswald. He received his Ph.D. in Computer Science from the Ernst-Moritz-Arndt University Greifswald in 2012 and his M.Sc. in Computer Science from Technische Universität Berlin in 2005.
Institut für Community Medicine, Ernst-Moritz-Arndt-Universität, Walther-Rathenau-Str. 48, 17475 Greifswald
Marko Rak is Ph.D. students in the Computer Vision Group at the Otto-von-Guericke-University Magdeburg. He received his M.Sc. in Computer Science in 2013. His research interests is on methods in large-scale medical image analysis.
Fakultät für Informatik, ISG, Otto-von-Guericke-Universität, Universitätsplatz 2, 39106 Magdeburg, Germany
Charlotte Winkler is Ph.D. students in the Computer Vision Group at the Otto-von-Guericke-University Magdeburg. She received her M.Sc. in Bioinformatics from the Freie Universität Berlin in 2010. Her research interests are model-based image segmentation for application in medical images.
Fakultät für Informatik, ISG, Otto-von-Guericke-Universität, Universitätsplatz 2, 39106 Magdeburg, Germany
Paul Klemm is Ph.D. student in the Visualization group at the Otto-von-Guericke-University Magdeburg and received his M.Sc. in Computational Visualistics in 2012.
Fakultät für Informatik, ISG, Otto-von-Guericke-Universität, Universitätsplatz 2, 39106 Magdeburg, Germany
Bernhard Preim is professor for “Visualization” at the computer science department at the Otto-von-Guericke-University of Magdeburg, heading a research group which is focused on medical visualization and applications in diagnosis, surgical education and surgery planning. He received the Diploma in Computer Science in 1994 (minor in Mathematics) and a Ph.D. 1998 (both from the University of Magdeburg) and a habilitation degree from the University of Bremen, 2002.
Fakultät für Informatik, ISG, Otto-von-Guericke-Universität, Universitätsplatz 2, 39106 Magdeburg, Germany
Henry Völzke is professor and head of the Institute for Community Medicine, Section SHIP-KEF at the Ernst-Moritz-Arndt University Greifswald. Between 1987 and 1993. Henry Völzke studied Human Medicine at the Universities Greifswald, Leipzig and Maastricht. He is certificated specialist for Internal Medicine and professor for Clinical Epidemiology at the Institute for Community Medicine Greifswald, Germany.
Institut für Community Medicine, Ernst-Moritz-Arndt-Universität, Walther-Rathenau-Str. 48, 17475 Greifswald
©2015 Walter de Gruyter Berlin/Boston
