[Insight-users] CT Artifact Segmentation

[Neil Panjwani]

Hi,

I need some help with a CT imaging artifact. I'm working on a stool
subtraction project of the colon in which the stool is tagged near 700 HU
(bright), air is -1025 HU (dark) and tissue is grey in the range of -300-400
HU (depending on the proximity to stool).

I'm trying to separate stool-air boundaries from stool-tissue-air
boundaries. The problem arises because of the partial volume effect of CT
imaging. At the stool-air boundary, the intensity is blurred and mimics
tissue as the intensity goes from very negative to very positive. The same
occurs during a stool-tissue-air boundary, however the change is less abrupt
due to the inner tissue layer.

I've tried using a connected component from known tissue but I erroneously
connect stool-air as tissue in the process. I've tried intensity and
gradient magnitude thresholds but the intensity-gradient relationship for
the two cases are nearly identical. The gradient is very sensitive to my
choice of sigma; values too large lose the tissue altogether and values too
low keep too much noise. I've also tried directional gradients, moving
outward from air (dark), but again the choice of sigma makes it extremely
sensitive.

I have also tried using local Haralick texture features (in the OTB
toolbox), but haven't seen good results. I've only tried a few offset pairs.
I try to avoid computing all offsets and averaging because it is incredibly
slow to generate all the GLCM histograms.

I've attached the original input and my voxel map, based on simple intensity
and gradient thresholds, as well as zoomed in versions illustrating the
problem. Here, orange represents tissue, black is stool, blue is air, and
white is unclassified. As can be seen in map_zoom.png, tissue which is
bordering both stool and air in the center of the image is left
unclassified.

How can I distinguish these two boundaries in order to recover the
unclassified tissue?
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