Submitted by user11532 t3_yk591e in MachineLearning
clementiasparrow t1_iutfviu wrote
I know nothing about this field but here is an idea a bit out of the ordinary. I couldn’t help it :)
If you can get instance segmentation to work on fibers in a voxel of some small size, you could dice it into subvoxels and create a graph that links fiber segments to other segments of the same fiber in other neighboring voxels. Now it becomes a link-prediction problem on a graph. If you can associate some mask with the fiber segments through instace segmentation, you could feed a. the local voxel-coordinates, b. the local image data and c. the mask as node-data for each fiber-sement-node. Now you could try some fancy GNN link predictors on the local area of voxels and see if it will connect fiber segments correctly.
Hope you at least got a good laugh and good luck!
user11532 OP t1_iv06tvl wrote
Any ideas are appreciated. :)
If I understand you correctly, this would be a way to merge the results for smaller parts of an image? Unfortunately, I haven't really managed to achieve any good results on such smaller image parts either. For that reason I haven't tested the merging algorithm presented in the paper, so I don't know how well that one works.
clementiasparrow t1_iv12zuu wrote
Ok. If you cant annotate, it gets difficult … Maybe stack three depth layers (if there is more than one) and interpret as rgb channels. Then it may be easier to visually track fibers that go in and out.
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