[Insight-users] Chest CT Segmentation

[Luis Ibanez]

Hi Henky,

Here are some ITK algorithms that you may
want to try out for segmenting Lung from CT.


1)  Watersheds.
     Please look at the example in the software guide

     http://www . itk . org/ItkSoftwareGuide . pdf

     Section 9.2 pdf-page 356.

     You should compute the GradientMagnitude of the
     CT image and then run Watersheds in this output.


2)  ThresholdSegmentationLevelSet
     You will find this method described in
     http://www . itk . org/ItkSoftwareGuide . pdf
     Section 9.3.4, pdf-page 386.



3)  FastMarchingLevelSet
     It is described in Section 9.3.1, pdf-page 365.
     http://www . itk . org/ItkSoftwareGuide . pdf
     If you find that FastMarching produces leaks
     you can move to refine the level set using
     the GeodesicActiveContour filter described in
     Section 9.3.3, pdf-page 380.



An easy way to experiment with these algorithms
is ot use the free version of VolView and run
the ITK plugins that you will find in the
"View->Filters" menu.

You can download VolView for free from

   http://www . kitware . com/products/volview . html

Once you find good parameters for segmenting your data
set you can reproduce a pipeline in your own application.


You will also find useful to look at the applications
available in the InsightApplications checkout.

In particular to:

   - The SegmentationEditor (Watershed)
   - SNAP (manual segmentation + Level Sets)


NOTE that LevelSet algorithms expect your data to be
represented with isotropic pixels. Chest CT is usually
anisotropic. You may want to use the program

  Insight/Examples/Filtering/ResampleVolumesToBeIsotropic.cxx

in order to convert your CT to isotropic pixels.



Please let us know if you have further questions,



Thanks,



    Luis



------------------------------
Henky Wibowo wrote:

> Hello,
> 
> Can anyone give me a suggestion as which segmentation algorithm would do
> well in segmenting the lung region in a stack of CT scan?
> 
> Thanks,
> 
> Henky
> 
> 
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