Eidolon: Visualization and Computational Framework for Multi-modal Biomedical Data Analysis

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Biomedical research, combining multi-modal image and geometry data, presents unique challenges for data visualization, processing, and quantitative analysis. Medical imaging provides rich information, from anatomical to deformation, but extracting this to a coherent picture across image modalities with preserved quality is not trivial. Addressing these challenges and integrating visualization with image and quantitative analysis results in Eidolon, a platform which can adapt to rapidly changing research workflows. In this paper we outline Eidolon, a software environment aimed at addressing these challenges, and discuss the novel integration of visualization and analysis components. These capabilities are demonstrated through the example of cardiac strain analysis, showing the Eidolon supports and enhances the workflow.
Original languageEnglish
Title of host publicationMedical Imaging and Augmented Reality: 7th International Conference, MIAR 2016, Bern, Switzerland, August 24-26, 2016, Proceedings
PublisherSpringer International Publishing
Number of pages13
ISBN (Electronic)9783319437750
Publication statusPublished - 2016

Publication series

NameLecture Notes in Computer Science


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