Publikationen nach Jahren

The study and analysis of relationships in a complex and multi-scale data set is a challenge of information and scientific visualization. This work proposes an integrated visualization to capture all the important aspects of multi-scale data into the same view by leveraging the multi-scale biomedical knowledge encoded into an underly- ing ontology. Ontology supports visualization by providing semantic means to identify relevant items that must be presented to the user. The study and analysis of relationships across the scales are presented as results of queries to the multi-scale biomedical knowledge space. We demonstrate the prototype of the graphical interface of an integrated visualization framework and the knowledge formalization support in an example scenario related to the musculoskeletal diseases.

The need for handling huge amounts of data from several sources is becoming increasingly important for biomedical scientists. In the past, there were mainly different modalities in imaging techniques that had to be combined. Those modalities usually measured different physical effects from the same object and shared dimensions and resolution. Nowadays, an increasing number of complex use cases exist in biomedical science and clinical diagnostics that require data from various domains, each one related to a different spatiotemporal scale. Multiscale spatial visualization and interaction can help physicians and scientists to explore and understand this data. In the recent years, the number of published articles on efficient scientist-centric visualization and interaction methods has drastically increased. This chapter describes current techniques on multiscale visualization and user interaction and proposes strategies to accommodate current needs in biomedical data analysis.