Hi,
I'm working on a project where I have to segment out nucleus of cells in a
volume. I use random_walker with define markers for every nuclei. If I try
to run it on the all volume the segmentation works well but it's very slow.
So I used util.view_as_blocks function from scikit to split my image and
markers and I loop over the different block using joblib:
rw_dapi_chunks = Parallel(n_jobs =
4)(delayed(segmentation.random_walker)(chunks[i,j],
chunks_markers[i,j], beta = 3000,
mode='cg_mg') for
i in range(2) for j in range(2))
So I end up with a list of 4 images and if I combine these images (btw I'm
not sure what is the best way for doing that? I just add them up in an
empty array) everything work well, except that I end-up with nuclei with 2
different labels:
[image: Images intégrées 1]
Am I doing something wrong? Is there a way to split your images in block
for parallel computing but being able to get the labeling right at the end?
Best,
Cedric
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