An Out-of-Domain Synapse Detection Challenge for Microwasp Brain Connectomes

Jingpeng Wu; Yicong Li; Nishika Gupta; Kazunori Shinomiya; Pat Gunn; Alexey Polilov; Hanspeter Pfister; Dmitri Chklovskii; Donglai Wei

arXiv · 2302.00545

An Out-of-Domain Synapse Detection Challenge for Microwasp Brain Connectomes

Jingpeng Wu·Yicong Li·Nishika Gupta·Kazunori Shinomiya·Pat Gunn·Alexey Polilov·Hanspeter Pfister·Dmitri Chklovskii·Donglai Wei

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Abstract

The size of image stacks in connectomics studies now reaches the terabyte and often petabyte scales with a great diversity of appearance across brain regions and samples. However, manual annotation of neural structures, e.g., synapses, is time-consuming, which leads to limited training data often smaller than 0.001\% of the test data in size. Domain adaptation and generalization approaches were proposed to address similar issues for natural images, which were less evaluated on connectomics data due to a lack of out-of-domain benchmarks.

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Jingpeng Wu, Yicong Li, Nishika Gupta, Kazunori Shinomiya, Pat Gunn, Alexey Polilov, Hanspeter Pfister, Dmitri Chklovskii, Donglai Wei. 2023-02-01. An Out-of-Domain Synapse Detection Challenge for Microwasp Brain Connectomes. https://arxiv.org/abs/2302.00545

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