Imperial College London


Faculty of EngineeringDepartment of Computing

Head of Department of Computing



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BibTex format

author = {Kerfoot, E and Fovargue, L and Rivolo, S and Shi, W and Rueckert, D and Nordsletten, D and Lee, J and Chabiniok, R and Razavi, R},
doi = {10.1007/978-3-319-43775-0_39},
pages = {425--437},
title = {Eidolon: Visualization and computational framework for multi-modal biomedical data analysis},
url = {},
year = {2016}

RIS format (EndNote, RefMan)

AB - © Springer International Publishing Switzerland 2016. 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.
AU - Kerfoot,E
AU - Fovargue,L
AU - Rivolo,S
AU - Shi,W
AU - Rueckert,D
AU - Nordsletten,D
AU - Lee,J
AU - Chabiniok,R
AU - Razavi,R
DO - 10.1007/978-3-319-43775-0_39
EP - 437
PY - 2016///
SN - 0302-9743
SP - 425
TI - Eidolon: Visualization and computational framework for multi-modal biomedical data analysis
UR -
ER -