SPHERICALHOUGH detects spherical structures from 3D images. Determines object centers and radii and outputs image mask of centers and spheres. This hough transform is based on the gradient field of the image. The code is heavily based off of Circular Hough Transform by Tao Peng (see info below).
Run Example.m to see demonstration of SphericalHough on 3D MRI data of a rat kidney. It demonstrates the detection of kidney glomeruli, which are roughly spherical at 31x31x31 um^3 resolution. The expected radii are between 2 to 7 pixels. Example data is from the following article: MRH of age-related nephropathy, Tox Path, 2012 Jul;40(5):764-78 (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3515870)
Supplemental material is also available on CIVMspace: http://www.civm.duhs.duke.edu/lx201107
Essential support functions are included for the example. Complete support functions can be found at the websites below:
2007_03_07 original Circular Hough Transform by Yao Peng
2010_08_25 Spherical Hough Transform by Brian Hulette
2014_10_20 simpification, filtration, image mapping, classifiers, and example by Luke Xie
Luke Xie (2022). Spherical hough transform for 3D images (https://www.mathworks.com/matlabcentral/fileexchange/48219-spherical-hough-transform-for-3d-images), MATLAB Central File Exchange. Retrieved .
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