Today, it is possible to scan the human body very precisely with the help of x-ray CT images. These CT images are based on voxels. If you look closely at CT images of lung lobes, you can see five lobes segments, the right lung is divided into three lobes segments and the left lung is divided into two lobes segments. The MIP method is one of the most used techniques to define a slap thickness and visualize the desired 2D rendering voxels of lung lobes.
The biggest challenge in this case is how to delete or correct an exact location or a false segmentation of lung lobes without affecting the whole lobes segmentation?
is there a mech technique (like Delaunay Triangulation), which can mesh the entire 2D rendering lung lobesand then select and delete or correct the exact location manually without affecting the lobes segmentation?
This question has been unanswered for a long time.
for clarification , do you mean how to get a CT image which better reflects real tissue anatomy or theoretically how to recalculate images from available images.
I think it would depend on the data storage capacity of instrument used.
eg you could recalcuate using more points or different aborbance levels or finer numerical approximations in FFTs..
Thank you James Leigh .
So, I have generate volume mesh (isosurface extraction) from segmented CT lung lobes (.raw file) 512x512x207 8 bit using marching cubes algorithm. the loung lobes are segmented from 1 to 5 grayscale.
Now I am trying to generate a separate mesh for each lobe in one processing time that I can edit or make manual changes to a single lobe without affecting the entire lung lobe.
How to model grayscale segmented Lung lobe with individualized surface meshes?
Thank you
the attached paper may be helpful.
there are also other answer threads on RG.
eg under Sneha Mohane
Thank you. I have already read this paper but it does not help me as I have already created a volume mesh from a CT scan with Marching Cubes. My problem now is to model a segmented lung with individualised surface meshes, as in the following paper:
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