[Insight-users] Running the FastMarchingImageFilter.cxx example on 3D data

[Abayiz]

Hi Francesco, 


Fast marching computes the arrival time of a front at the points of a discrete lattice. In your case, your input first will be smoothed by "CurvatureAnisotropicDiffusionImageFilter", then its output will be given to the "GradientMagnitudeRecursiveGaussianImageFilter" to calculate its gradient. "Sigma" should be set to this filter (you can take a look at the gradient calculation formula). 


The output of this gradient filter is then given to the sigmoid filter to calculate its linear transformation, which requires you to provide alpha and beta. I usually set sigma=1.0, alpha=-2.0, beta=2.0 for my own case, but you should get suitable value by practice. Then this sigmoid output will be the input to your fast marching filter. The output of your fast marching filter is then given to a binary thresholder to obtain final binary output. You should set stopping and threshold values by yourself, usually with not a large number, and stopping value is larger than threshold value. 

Abayiz 




________________________________
 From: Mr Francesco Grussu <francesco.grussu at eecs.qmul.ac.uk>
To: insight-users at itk.org 
Sent: Friday, June 8, 2012 7:02 PM
Subject: [Insight-users] Running the FastMarchingImageFilter.cxx example on 3D data
 
Dear all,
I am trying to run the FastMarchingImageFilter.cxx example from the ITK
Software Guide 2.4.0 ( http://www.itk.org/ITK/resources/software.html ) in
order to apply a Fast Marching Level Set Segmentation on my own data.

My data are a stack of 260 512x512 2D slices stored in a .nrrd file coming
from a DICOM series. I have successfully modified the code of the
FastMarchingImageFilter.cxx example (which deals with a 2D image) in order
to handle 3D data...

The grey level of the voxel are stored as floating point data and range
from about -1000 to just under +2000.

I now the three coordinates of a suitable seed point, but I have no idea
about the other parameters (sigma, alfa, beta, Time Threshold, Stopping
Value as well as the parameters for the
CurvatureAnisotropicDiffusionImageFilter called int the example).

Does anyone have even a rough idea about a suitable way to estimate good
values of that parameters before running the algorithm?

Thanks a lot in advance,
my regards,

Francesco



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