Hidden Markov Modeling for Maximum Likelihood Neuron Reconstruction. (arXiv:2106.02701v4 [cs.CV] UPDATED)

Web: http://arxiv.org/abs/2106.02701

Recent advances in brain clearing and imaging have made it possible to image
entire mammalian brains at sub-micron resolution. These images offer the
potential to assemble brain-wide atlases of neuron morphology, but manual
neuron reconstruction remains a bottleneck. Several automatic reconstruction
algorithms exist, but most focus on single neuron images. In this paper, we
present a probabilistic reconstruction method, ViterBrain, which combines a
hidden Markov state process that encodes neuron geometry with a random field
appearance model of neuron fluorescence. …

arxiv cv markov modeling