I want to segment the turbinates from a canine. Turbinates are typically thin interconnected tissue/bone . I’m using the mask volume segmentation tool & Paint to isolate the turbinates from the bones of the skull. My segmentation is not interconnected. Is this the correct segmentation tool to use or how would you interconnect the tissue?
These bones are so thin that due to partial volume effect they may be hardly distinguishable from image noise at usual CT resolutions. What is your overall goal - rendering, 3D printing, quantitative analysis, …? What are your time constraints (how many data sets do you need to process and much time you can spend with each)?
My goal is to 3D print the turbinates in the skull to show the reduction of the nasal cancer from stereotactic radiation treatment. The nasal cancer was much easier to segment/print as it was a mass filed with mucosa. I segmented that by setting the threshold values and using Paint. The turbinates are so thin, I’m thinking I will need to thicken them internally so I can print them. I will have two segmentations-the skull and turbinates. I have a week to segment the turbinates and print both sides of the skull.
If you only going to do this one, and anatomical accuracy is important, I think manual segmentation is the way to go. Your initial segmentation seems to based on thresholding, and such it is a mixture of things including turbinates, cartilage, but also missing for some reason part of ethmoid plate and smaller turbinals.
While they are complex, the morphology changes gradually from slice to slice. If you carefully outline in a one slice using manual paint/draw options, skip a few and do the same on another, you can use the ‘fill between slices’ to interpolate skipped sections.
This of course doesn’t work very well, if you are going to do this routinely.
Then perhaps you can play with the segmentation geometry
I agree, if it is a one-off then the fastest solution overall is to use manual or semi-automatic methods. You could try to experiment with various preprocessing methods or developing more sophisticated workflows but that does not pay off if you only need to segment one or a few cases.
In addition to the Fill between slices effect, you can also try to use Paint effect with sphere option enabled (so that it paints on a couple of slices at once) with enabling “Editable intensity range” in Masking settings. You can find a good intensity range using Threshold effect (click “Use for masking” if the previewed intensity range looks good).
Hi, thanks for your reply. I will try the “fill between slices” option. I plan to do this on multiple patients. So, I will need to find a faster way after this project. I’ll try to slice it in multiple views so as to get a better build/connections in all directions when using fill between slices. There is a Perk Lab video for a femur by using the mask region growing, paint, grow from seeds, I will try it as well.
Great, I appreciate the help from everyone.
I will try your suggestions and let you know how it goes.
Region growing requires the segmented structures to be at least 4-6 voxel thick. You can achieve that by Cropping and resampling the volume (resample with spacing scale of 0.2 to 0.7, crop to prevent the segmentation to consume too much memory - spacing scale of 0.5 increases memory usage and processing time by a factor of 8x).
Hi Murat and Andras,
I was successful in segmenting the turbinates using fill between slices.
Is there a setting to reduce the volume of the fill or ratio of negative to positive space in fill between slices? I was hoping to develop the left nasal cavity with more detailed turbinate leaflets.
My axial view shows this detail but fill between slices filled all the negative space. This is for 3d printing. Any suggestions? Thanks!
You can always a good segmentation with “Fill between slices” by reviewing the slices after clicking “Preview” (before clicking “Apply”) and if you find that on any slice the segmentation needs improvement then segment that slice, too. This will automatically recompute the segmentation, taking into account this additional input. Click “Apply” when the entire segmentation is acceptable.
Thanks, I’ll give it a go.