I have a stack of CT images from a whole body scan of live pigs. I
want to remove internal organs and perform a virtual dissection of
each pig. The image stack is a data matrix or cube of size 512 x 512 x
1200, where each image is a 512 x 512 matrix, and the total number of
images per pig is approx. 1200.
I have tried som different strategies so far:
1. Thresholding by gray values
Each tissue have different gray values, and it is easy to separate
soft tissues (fat, muscle, internal organs) from cartilage (bone). The
problem is to separate the soft tissues from each other, especially
muscle tissue from internal organs like kidney, liver, stomach etc.
They have the same gray values.
2. *****on / dilation
The next step was to segment the tissues based on *****on / dilation.
This works well when there are solid or clear boundaries between
internal organs and muslce tissue separated by the body cavity. But it
is not possible to separate when the boundaries are more diffuse, i.e.
kidneys and liver connected to the body cavity.
3. Active contour / "s****s"
Recently, I have tried to use active contours or "s****s" by inserting
seed points along the body cavity. This have worked pretty well, and I
am able to perform the segmentation in a semi-automatic way. For 3D
segmentation along the saggital or coronal plane of the animal, I have
extrapolated the seed points and make new ones when the anatomy of the
animal changes. Total process time for this procedure is approx 8-10
minutes per pig.
I want to reduce process time and automate this procedure even further
by reducing the manual labour of seed point according to anatomy in
the saggital / coronal direction. I wish I could attach a picture, but
you can view some image examples at this external web site (google
search: CT image, pig):
http://cmiss.bioeng.auckland.ac.nz/development/examples/a/as/index.html
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