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Hierarchical Manifold Clustering on Diffusion Maps for Connectomics (MIT 18.S096 final project)
[article]
2016
arXiv
pre-print
In this paper, we introduce a novel algorithm for segmentation of imperfect boundary probability maps (BPM) in connectomics. Our algorithm can be a considered as an extension of spectral clustering. Instead of clustering the diffusion maps with traditional clustering algorithms, we learn the manifold and compute an estimate of the minimum normalized cut. We proceed by divide and conquer. We also introduce a novel criterion for determining if further splits are necessary in a component based on
arXiv:1607.06318v1
fatcat:bxn2s7p6sngwlc6ng3hpaowhqy