Hi all, (@
I am trying to wrap my head around the Isotropic Reconstruction Example at
Namely this cell
anisotropic_transform = anisotropic_distortions ( subsample = 10.2, psf = np.ones((3,3))/9, # use the actual PSF here psf_axes = 'YX', )
I have a hard time understanding what the PSF here is supposed to be…
The idea is that, under the assumption that the data would look the same if we were to observe it in XY, XZ or any arbitrary slice, we use the 2D XY plane (with a good sampling) to recover what is lost in the Z plane (where there is anisotropy)
So to do that, we take the XY planes which we use as ground truth, and generate XZ planes by applying an anisotropic distortion to it, so that this serves as raw data.
We define the anisotropy factor, which represents the difference in XZ versus Z sampling,
We give it a PSF
I have a hard time understanding the shape of the PSF we have to give it.
- Is it an actual PSF in XYZ? The example here shows a 2D PSF which I assume is along the XY axes, which will then be ‘stretched’ to compute the simulated raw data?
- The PSF shape can be rather different in the axial direction, so how should I take it?
- How should I normalize the PSF? Sum of intensities equal to 1? Max intensity=1?
- The example shows a PSF of size 3x3. What is a good size to use, as this is extremely small.
- Is the PSF we are giving it isotropic in XYZ? (or XZ?) if so, should it be the same voxel (pixel) size as the original image?
This is a bit of a start of my questions. Any help would be appreciated