ParaGlyder: Probe-driven Interactive Visual Analysis for Multiparametric Medical Imaging Data

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12221)


Multiparametric imaging in cancer has been shown to be useful for tumor detection and may also depict functional tumor characteristics relevant for clinical phenotypes. However, when confronted with datasets consisting of multiple values per voxel, traditional reading of the imaging series fails to capture complicated patterns. These patterns of potentially important imaging properties of the parameter space may be critical for the analysis, but standard approaches do not deliver sufficient details. Therefore, in this paper, we present an approach that aims to enable the exploration and analysis of such multiparametric studies using an interactive visual analysis application to remedy the trade-offs between details in the value domain and in spatial resolution. This may aid in the discrimination between healthy and cancerous tissue and potentially highlight metastases that evolved from the primary tumor. We conducted an evaluation with eleven domain experts from different fields of research to confirm the utility of our approach.


Medical visualization Visual analysis Multiparametric medical imaging data 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of InformaticsUniversity of BergenBergenNorway
  2. 2.Mohn Medical Imaging and Visualization CentreHaukeland University HospitalBergenNorway
  3. 3.Department of Clinical MedicineUniversity of BergenBergenNorway

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