Comments (3)
the result of find_centerCol is error in truth data.
from leap.
Currently LEAP has no algorithm to estimate centerRow. Image quality usually degrades weakly with centerRow errors and thus it is a hard parameter to estimate. In the past I have implemented algorithms to estimate this, but have never been too impressed with their accuracy. Usually this parameter is estimated with a calibration scan, like a stack of metal balls. Anyway, if you know of a good algorithm to estimate centerRow, please let us know about it.
For you second question, I will need more detail. Could you send me a copy of the output from: leapct.print_parameters() and post an image of one of the projections.
from leap.
I've tested the find_centerCol algorithm with multiple real CT data sets and it seems to be working great for me.
Note that it only works for parallel-, fan-, and cone-beam CT geometry types (i.e., everything but modular-beam) and the projections cannot be truncated on the right or left sides. If you have any bad edge detectors, these must be cropped out before running this algorithm. I also added more comments to this algorithm to help you run it successfully. These can be viewed here:
https://leapct.readthedocs.io/en/latest/
I am going to close this issue because I have not heard back in a long time and I think I resolved the issue, but feel free to open a new issue if you want.
from leap.
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from leap.