3D Spatial Autocorrelation Function for Anisotropy

Posted by Michael Doube on Apr 28, 2009; 4:51pm
URL: http://imagej.273.s1.nabble.com/3D-Spatial-Autocorrelation-Function-for-Anisotropy-tp3692740.html

Hi all

I've been working on a plugin that calculates anisotropy in 3D using the
  mean intercept length, which seems to work OK.  I've come across
another method that uses spatial autocorrelation, which has the
advantage that segmentation is not required.

http://dx.doi.org/10.1118/1.2437281

I remember there was chat earlier this month about 1D autocorrelation,
which might work (i.e. work out the autocorrelation function of line
probes at a range of angles through the stack) but the paper I've read
states that anisotropy can be worked out faster using k-space data from
magnetic resonance imaging.  I'm a bit confused as I though that k-space
data were essentially Fourier transformations of 2D images, so you get
your 2D cross-sectional image by doing an inverse Fourier transform on
the k-space data.  Additionally, I don't have MRI k-space images, I have
microCT images...

So does the method I'm reading propose that I work out the 3D Fourier
transform of a stack, then work out the ACF at each 3D angle?

Any insight here would be appreciated,

Mike