First experiments in surface-based mechanical property reconstruction of gelatine phantoms
A. Peters, S. Wortmann, R. Elliott, M. Staiger,J.G. Chase, E.E.W. Van Houten
Digital Image-based Elasto-Tomography (DIET) aims to be a low-cost alternative to current breast cancer screening modalities
Based on elastographic principles and low-cost digital imaging techniques
Introduction
The DIET System
[1] Peters et. al, JSME Int. Journal, (2004)
Four major steps in the DIET system
Actuate Capture Process Reconstruct
Simulation studies undertaken have proven the concept of surface-based mechanical property reconstruction[1]
Cylindrical tissue-approximating gelatine phantoms
Actuation achieved using dSPACETM, laser interferometer, linear voice-coil actuator with amplifier
Methods
Phantom Studies
Motion captured using two consumer-level digital cameras
Manually-applied dots on tracked on phantom surface
Real motion approximated with a least-squares fitted ellipsoid
Finite Element (FE) model of cylinder created and meshed
Actuated with same constraints as real gelatine phantom
Sparse parallel direct matrix inversion and solution performed with MUMPS[2] and Goto BLAS[3]
Methods
FE Simulation
Projecting a measured motion point back to the surface of a 3D mesh to allow motion comparison
[2] Amestoy et. al, Parallel Computing, (2005) [3] http://www.tacc.utexas.edu/resources/software/
Forward FE simulation performed at small intervals over a range of homogeneous stiffness values
Results
Simulated Motion
Sample displacement solutions at a range of
stiffness values
Testing showed 22k node mesh solutions were converged at 10kPa and above
Results
Motion Error Sweep
Qualitative comparison made between actual motion and simulated phantom motion at 27kPa
Results
Direct Comparison
Homogeneous gelatine phantom stiffness successfully identified using steady-state
motion measurements and a FE model
MEASURED SIMULATED27kPa
Damping and phase
Material non-linearity
More advanced reconstruction Multiple parameters Gradient-descent Genetic algorithm/simulated annealing
Tighter integration of motion capture and processing
Acknowledgements PhD supervisors
Data collection Jérôme Rouzé & Arnaud Milsant Edouard Ravini & Fabrice Jandet
Conclusions
Current Challenges