[Insight-users] Are there segmented visible human data?

[Luis Ibanez]

Hi Weiguang,


1) You will find products with labelled images
    from the Visible Human and Visible Woman
    datasets in the NLM-NIH page:

http://www.nlm.nih.gov/research/visible/products.html

    You will also find animations and didactic material at

http://www.nlm.nih.gov/research/visible/animations.html



2) Yes, we have segmented structures such as

              Liver, Lungs and Heart

    BUT !!!

    Note that segmentation is an *ILL-POSED* problem.

    There is no such thing as "the segmentation" of an organ.
    Instead you can only get "a segmetation" of an organ.

    This means that there are many techniques and many
    parameters for each segmentation technique. If you
    want to avoid frustration in your segmentation
    endeavors you *MUST* first clearly define the
    purpose of your segmentation efforts, so you have a
    criterion that tells how much is "good enough".

    A full segmentation of an anatomical structure is
    rarely feasible. This is due to the continuous
    nature of biological tissues, and the fact that
    organs are ultimately made out of cells.


    The only real segmentation method is "Dissection"
    You don't want to do that unless you are an M.D.    :-)



3) To address you question:

    Here are some recomendations of segmentation "recipies"
    since segmentation is not a science but rather and art
    quite similar to cooking:


    Lung:  get CT data sets,
           and use the itkOtsuThresholdImageFilter
           followed by itkConnectedThresholdImageFilter.
           be prepared to smooth them with Erosion/Dilation
           and/or BinaryMedian filter.


    Liver:  get CT data sets, *avoid* large interslice spacings.

           - use Watershed
           - or use ThresholdSegementation Level Set
           - or use FastMarching Level Set

           Beware that a liver is composed of several
           segments and that the anatomical shape of the
           Liver is *very* variable, since the liver is
           actually filling in the space left by other
           organs.


    Heart:  CT or MR could be used, but note that the distinction
            between the muscle walls and the surrounding organs
            is quite subtle.

            Reject energetically any datasets that has traces
            of motion artifacts. Keep in mind that cardiac MR
            is acquired by takin one slice per carciac cycle
            so technically speaking each slice is in a different
            time, although they are (hopefully) in the same phase
            of the cardiac cycle.

            Note also the "heart" is a very complex organ.
            You *must* decide whether your definition of heart
            include the connected veins and arteries or not
            and whether you want to get the details of both
            the internal and external walls.


    Spleen: sorry no recipy for spleen, except the warning
            the is very close to the liver and very similar
            in intensities in CT.



About using RGB data, yes, that helps, but beware that color
doesn't always have as much information as the human eyes+brain
tend to believe.  You will find multiple methods in ITK for
segmenting color images. They include

       Region growing
       Statistical classification
       Fuzzy connectedness
       Watersheds


The images in the cover of the ITK software guide were segmented
from the CT and RGB dataset of the Visible Woman.


Keep in mind that once you "think" that you are done with
your segmentation, your supervisor is going to ask you for
the "Validation". At that point you will ask yourself why
you didn't went to Law school or rather formed a music band
instead of working in medical imaging.

The current standards for validation come down to comparing
your segmentation with the ones produced by human operators
using delineation methods.


Before you start writing code, get an Anatomy Atlas, and
have a chat with a doctor. That will help you understand
the structures that you are trying to segment and what
pieces of them are really important.



    Regards,


       Luis



---------------------
Weiguang Guan wrote:

> Hi ITK users,
> 
> Is there a well-labeled visible human image data (each voxel is classified
> to as the organ or tissue it belongs to), either as a commercial product
> or in public domain? I would appreciate it very much if you could give me
> some information. Thank you very much in advance.
> 
> Has anyone succeeded in segmenting liver, kidney, heart, spleen out
> of 3D CT scan with ITK? Do you think it would be easier to segment them in 
> MRI or visible RGB images than in CT? 
> 
> Weiguang
>