[Insight-users] watershedImageFilter parameters for 3D CT images

[Luis Ibanez]

Hi Gator,

What I meant is that, usually the watershed segmentations produced by
a single water level are not perfect. At low water levels you usually get
big chunks of the structures that you want to segment, but they are missing
detailed pieces.  If you raise the water level, then you get a lot more small
pieces.

Therefore, it is common to have to take, some of the big chunks produced
at low water levels and OR them (logical or) with the some selected smaller
pieces that are produced at higher water levels.

You may find useful to play with the application:

    InsightApplications/StreamedWatershedSegmentation


   Regards,


            Luis


--------------------------------------------------
On Mon, Nov 2, 2009 at 2:29 PM, Gator Philly <gatoratphilly at gmail.com> wrote:
> Hi Luis,
>
> Thanks a lot for your helpful suggestions. For the point (6), what do you
> mean by saying "t is common to have to construct your segmentation   by
> combining fragments that are extracted at different     water levels" ? Do
> you mean I need some
> connectedcomponentImageFilter after watershedImageFilter to combine
> fragments?
>
> Thanks again!
> gator
>
> On Sun, Nov 1, 2009 at 4:53 PM, Luis Ibanez <luis.ibanez at kitware.com> wrote:
>>
>> Hi Gator,
>>
>> 1) Yes, if you are working on a  CT Image, it tends to be useful
>>     to do some denoising before running a Watershed filter.
>>
>>
>> 2) A rule of thumb is to set the Threshold to be about 1 / 100
>>     of the Level.
>>
>>
>> 3) Typical values of level are 0.2 ~ 0.3.
>>
>>     But of course, they vary with the structure that you want to
>>     extract, and the image that you are providing as input
>>
>>
>> 4)  Please not that usually you want to run the watershed filter
>>      not in the image directly but in its GradientMagnitude image,
>>      ... unless... you are lucky enough to be searching for an
>>     anatomical structure that is dark and it is fully surrounded by
>>     brighter objects.
>>
>>
>> 5) Finding a set of parameters that will work for a full set of
>>     images is a challenging problem, and it doesn't have a
>>     trivial answer.
>>
>>      What we can suggest you are tools for making this easier:
>>
>>       We have found effective to use
>>
>>                a) CMake Macros to define tests for each one
>>                     of the images in the set, and then run all the
>>                     tests by using ctest.
>>
>>                 b) Batchmake (www.batchmake.org).
>>
>>
>> 6)  Note also, that the watershed filter will rarely provide a
>>      segmentation solution by looking at a  single level.
>>      It is common to have to construct your segmentation
>>      by combining fragments that are extracted at different
>>       water levels.
>>
>>
>>
>>     Regards,
>>
>>
>>             Luis
>>
>>
>> --------------------------------------------------
>> On Fri, Oct 30, 2009 at 12:38 PM, Gator Philly <gatoratphilly at gmail.com>
>> wrote:
>> > Hello itk gurus,
>> >
>> > In order to effectively use watershedImageFilter, how to optimize those
>> > two
>> > parameters: Level and Threshold?
>> > If I have a multiple set of 3D CT images, each set of 3D CT images might
>> > have different voxel intensity characteristics,
>> > it seems from my experiments that one set of parameters for all sets
>> > might
>> > not the optimal solution. How can I
>> > choose the parameters based on the characteristics of given set?
>> >
>> > The other question I have is should I do some denoising pre-processing
>> > such
>> > as median filter before I do watershed?
>> >
>> > Thanks a lot for any suggestions and comments.
>> > Best,
>> > Gator
>> >
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