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

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.

[1]  D. Pennell,et al.  CMR of Ventricular Function , 2007, Echocardiography.

[2]  Sébastien Ourselin,et al.  A Comprehensive Cardiac Motion Estimation Framework Using Both Untagged and 3-D Tagged MR Images Based on Nonrigid Registration , 2012, IEEE Transactions on Medical Imaging.

[3]  Ulrich Neumann,et al.  Accelerating Volume Reconstruction With 3D Texture Hardware , 1994 .

[4]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[5]  Helko Lehmann,et al.  Robust left ventricular myocardium segmentation for multi-protocol MR , 2012, Medical Imaging.

[6]  W. Hundley,et al.  Assessment of ventricular function with cardiovascular magnetic resonance. , 2007, Magnetic resonance imaging clinics of North America.

[7]  William R. Mark,et al.  Cg: a system for programming graphics hardware in a C-like language , 2003, ACM Trans. Graph..

[8]  W. Hibbard,et al.  Interactivity is the key , 1989, VVS '89.

[9]  P. Boesiger,et al.  Accelerated whole‐heart 3D CSPAMM for myocardial motion quantification , 2008, Magnetic resonance in medicine.

[10]  Colin Studholme,et al.  An overlap invariant entropy measure of 3D medical image alignment , 1999, Pattern Recognit..

[11]  Rüdiger Westermann,et al.  Acceleration techniques for GPU-based volume rendering , 2003, IEEE Visualization, 2003. VIS 2003..

[12]  Henning Scharsach Advanced GPU Raycasting , 2005 .

[13]  Daniel Rueckert,et al.  Analysis of 3-D myocardial motion in tagged MR images using nonrigid image registration , 2004, IEEE Transactions on Medical Imaging.