The Fast Iterative Digital Volume Correlation Algorithm (FIDVC) is the next generation DVC algorithm providing significantly improved signal-to-noise, and large (finite) deformation (incl. large rotations and image stretches) capture capability at low computational cost (please see Bar-Kochba, Toyjanova et al., Exp. Mechanics, 2014 for more details).
The following implementation contains the Matlab m-files for our FIDVC algorithm. The FIDVC algorithm determines the 3D displacement fields between consecutive volumetric image stacks. To provide maximum user versatility the current version is the CPU-based version, which runs a little bit slower (~ 5 - 15 minutes/per stack) than the GPU-based implementation. As Matlab’s GPU-based subroutines become more efficient we hope to provide the GPU-based version at a later release date.
To run you need a compatible C compiler. Please see (http://www.mathworks.com/support/compilers/R2015a/index.html)
FIDVC requires a 3D stack to be read in, which depending on the volume size can require a large amount of RAM in Matlab.
Main files
Supplement m files from the MATLAB file exchange:
Example Run files
What are the requirements for the input 3D image stack?
Please refer to input 3D Image Stack Requirements.
Can I use FIDVC for finding displacement fields in 2D images?
No. But you can use qDIC, this is 2D version of FIDVC for finding displacments in 2D images.
@article{bar2014fast,
title={A fast iterative digital volume correlation algorithm for large deformations},
author={Bar-Kochba, E and Toyjanova, J and Andrews, E and Kim, K-S and Franck, C},
journal={Experimental Mechanics},
pages={1--14},
year={2014},
publisher={Springer}
}
For questions, please first refer to FAQ and Questions/Issues (make sure to look through the closed Issues too!). Add a new question if similar issue hasn't been reported. We shall help you at the earliest. The author's contact information can be found at Franck Lab.