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Synaptic Partner Assignment Using Attentional Voxel Association Networks

Author(s): Turner, Nicholas L; Lee, Kisuk; Lu, Ran; Wu, Jingpeng; Ih, Dodam; et al

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dc.contributor.authorTurner, Nicholas L-
dc.contributor.authorLee, Kisuk-
dc.contributor.authorLu, Ran-
dc.contributor.authorWu, Jingpeng-
dc.contributor.authorIh, Dodam-
dc.contributor.authorSeung, H Sebastian-
dc.date.accessioned2021-10-08T19:45:05Z-
dc.date.available2021-10-08T19:45:05Z-
dc.date.issued2020en_US
dc.identifier.citationTurner, Nicholas L., Kisuk Lee, Ran Lu, Jingpeng Wu, Dodam Ih, and H. Sebastian Seung. "Synaptic Partner Assignment Using Attentional Voxel Association Networks." 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI) (2020): pp. 1209-1213. doi:10.1109/ISBI45749.2020.9098489en_US
dc.identifier.issn1945-7928-
dc.identifier.urihttps://arxiv.org/pdf/1904.09947.pdf-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1jn7b-
dc.description.abstractConnectomics aims to recover a complete set of synaptic connections within a dataset imaged by volume electron microscopy. Many systems have been proposed for locating synapses, and recent research has included a way to identify the synaptic partners that communicate at a synaptic cleft. We reframe the problem of identifying synaptic partners as directly generating the mask of the synaptic partners from a given cleft. We train a convolutional network to perform this task. The network takes the local image context and a binary mask representing a single cleft as input. It is trained to produce two binary output masks: one which labels the voxels of the presynaptic partner within the input image, and another similar labeling for the postsynaptic partner. The cleft mask acts as an attentional gating signal for the network. We find that an implementation of this approach performs well on a dataset of mouse somatosensory cortex, and evaluate it as part of a combined system to predict both clefts and connections.en_US
dc.format.extent1209 - 1213en_US
dc.language.isoen_USen_US
dc.relation.ispartof2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)en_US
dc.rightsAuthor's manuscripten_US
dc.titleSynaptic Partner Assignment Using Attentional Voxel Association Networksen_US
dc.typeConference Articleen_US
dc.identifier.doi10.1109/ISBI45749.2020.9098489-
dc.identifier.eissn1945-8452-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/conference-proceedingen_US

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