Eidolon: Visualization and computational framework for multi-modal biomedical data analysis

Eric Kerfoot, Lauren Fovargue, Simone Rivolo, Wenzhe Shi, Daniel Rueckert, David Nordsletten, Jack Lee, Radomir Chabiniok, Reza Razavi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 (US)
Title of host publicationMedical Imaging and Augmented Reality - 7th International Conference, MIAR 2016, Proceedings
EditorsHongen Liao, Guoyan Zheng, Su-Lin Lee, Philippe Cattin, Pierre Jannin
PublisherSpringer Verlag
Pages425-437
Number of pages13
ISBN (Print)9783319437743
DOIs
StatePublished - 2016
Externally publishedYes
Event7th International Conference on Medical Imaging and Augmented Reality, MIAR 2016 - Bern, Switzerland
Duration: Aug 24 2016Aug 26 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9805 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Medical Imaging and Augmented Reality, MIAR 2016
Country/TerritorySwitzerland
CityBern
Period8/24/168/26/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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