Re: Fit sphere to planar circles
- From: trancemissionxxi@xxxxxxxxx
- Date: Wed, 8 Apr 2009 01:12:21 -0700 (PDT)
On Apr 7, 1:24 pm, "Sven" <sven.holco...@xxxxxxxxxxxxxxxxxx> wrote:
Hi all,
I'm trying to find the center and radius of a mostly spherical body in a voxel volume (femoral head in a CT scan, to be precise).
My approach so far has been to use hough circle detection in the area of interest, looped over each slice. This detection works best around the hemisphere (rather than pole) regions of the sphere, and I am using some logic to cull away any false positive circles detected by the hough transform.
My question is this: what is the best way to fit a sphere to a series of planar circles?
My data is currently in the form of:
circs = [...
240.5275 145.0197 -564.5000 20.5078;
241.1135 146.1915 -559.5000 22.8516;
241.1135 146.1915 -554.5000 23.4375;
241.6994 146.7775 -549.5000 23.4375;
241.1135 146.7775 -544.5000 22.2656;]
The columns are the X, Y, and Z locations of 5 circle origins, and their radii.
I'm confident that the average of the X and Y columns represent the X and Y sphere centre, but I don't know the best way to get the Z location.
A simple average of Z locations is inaccurate because the detected circles are not necessarily centrally detected along the Z-direction.
Any thoughts? Perhaps I could try to fit a curve to the radii values and find its peak, but I'm not sure how to fit anything robustly to so few data points.
Any help would be very welcome.
Thanks,
Sven.
Sven,
I have a similar problem and I abandoned the hough transform. I assume
you have grayscale images. What I do is replicate slices to bring z
resolution ~equal to xy resolution, then I do a fft convolution with a
spherical mask (there is an fspecial3 on file exchage, you need some
normalization though) at the radius of interest. If you don't know the
radius, you can iterate over multiple radii. Take the pixel
coordinates corresponding to the max of the convolution.
Any thoughts on/need of computing the entropy of the pixels within the
sphere without requiring a supercomputing center? I'm actively
researching this. Let me know if you want to chat more about this.
Thanks,
Trance.
.
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