<html><body><div style="color:#000; background-color:#fff; font-family:times new roman, new york, times, serif;font-size:12pt"><div><span>Hi </span>Francesco, <br></div><div><br></div><div>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). <br></div><div><br></div><div>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. </div><div><br></div><div>Abayiz <br></div><div><br></div><div><br></div><div style="font-family: times new roman,new york,times,serif; font-size: 12pt;"> <div style="font-family: times new roman,new york,times,serif; font-size: 12pt;"> <div dir="ltr"> <font face="Arial" size="2"> <hr size="1"> <b><span style="font-weight: bold;">From:</span></b> Mr Francesco Grussu <francesco.grussu@eecs.qmul.ac.uk><br> <b><span style="font-weight: bold;">To:</span></b> insight-users@itk.org <br> <b><span style="font-weight: bold;">Sent:</span></b> Friday, June 8, 2012 7:02 PM<br> <b><span style="font-weight: bold;">Subject:</span></b> [Insight-users] Running the FastMarchingImageFilter.cxx example on 3D data<br> </font> </div>
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Dear all,<br>I am trying to run the FastMarchingImageFilter.cxx example from the ITK<br>Software Guide 2.4.0 ( http://www.itk.org/ITK/resources/software.html ) in<br>order to apply a Fast Marching Level Set Segmentation on my own data.<br><br>My data are a stack of 260 512x512 2D slices stored in a .nrrd file coming<br>from a DICOM series. I have successfully modified the code of the<br>FastMarchingImageFilter.cxx example (which deals with a 2D image) in order<br>to handle 3D data...<br><br>The grey level of the voxel are stored as floating point data and range<br>from about -1000 to just under +2000.<br><br>I now the three coordinates of a suitable seed point, but I have no idea<br>about the other parameters (sigma, alfa, beta, Time Threshold, Stopping<br>Value as well as the parameters for the<br>CurvatureAnisotropicDiffusionImageFilter called int the example).<br><br>Does anyone have even a rough idea about a suitable way to estimate good<br>values of
that parameters before running the algorithm?<br><br>Thanks a lot in advance,<br>my regards,<br><br>Francesco<br><br><br><br>_____________________________________<br>Powered by <a target="_blank" href="http://www.kitware.com">www.kitware.com</a><br><br>Visit other Kitware open-source projects at<br>http://www.kitware.com/opensource/opensource.html<br><br>Kitware offers ITK Training Courses, for more information visit:<br>http://www.kitware.com/products/protraining.php<br><br>Please keep messages on-topic and check the ITK FAQ at:<br>http://www.itk.org/Wiki/ITK_FAQ<br><br>Follow this link to subscribe/unsubscribe:<br>http://www.itk.org/mailman/listinfo/insight-users<br><br><br> </div> </div> </div></body></html>