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Issue No.05 - Sept.-Oct. (2014 vol.34)
pp: 70-82
Paolo Angelelli , University of Bergen
Steffen Oeltze , University of Magdeburg
Judit Haasz , University of Bergen
Cagatay Turkay , University of Bergen
Erlend Hodneland , University of Bergen
Arvid Lundervold , University of Bergen
Astri J. Lundervold , University of Bergen
Bernhard Preim , University of Magdeburg
Helwig Hauser , University of Bergen
Medical cohort studies enable the study of medical hypotheses with many samples. Often, these studies acquire a large amount of heterogeneous data from many subjects. Usually, researchers study a specific data subset to confirm or reject specific hypotheses. A new approach enables the interactive visual exploration and analysis of such data, helping to generate and validate hypotheses. A data-cube-based model handles partially overlapping data subsets during the interactive visualization. This model enables seamless integration of the heterogeneous data and the linking of spatial and nonspatial views of the data. Researchers implemented this model in a prototype application and used it to analyze data acquired in a cohort study on cognitive aging. Case studies employed the prototype to study aspects of brain connectivity, demonstrating the model's potential and flexibility.
Data models, Data visualization, Visual analytics, Analytical models, Anisotropic magnetoresistance, Biomedical imaging, Medical services,visualization, heterogeneous data, medical visualization, interactive visual analysis, visual analytics, graphics, computer graphics
Paolo Angelelli, Steffen Oeltze, Judit Haasz, Cagatay Turkay, Erlend Hodneland, Arvid Lundervold, Astri J. Lundervold, Bernhard Preim, Helwig Hauser, "Interactive Visual Analysis of Heterogeneous Cohort-Study Data", IEEE Computer Graphics and Applications, vol.34, no. 5, pp. 70-82, Sept.-Oct. 2014, doi:10.1109/MCG.2014.40
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