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Tracking fluorescent objects through movies is a critical first step in quantifying electrical or molecular dynamics in cells. In many applications, it is necessary to track large numbers of fluorescent objects moving through tissue in a nonrigid manner. In this submission, we describe the use of a graph attention-based neural network to detect-and-link fluorescent neuronal nuclei in the brain of freely behaving worms (C. elegans). This approach allows us to reliably match on average 33% of the cells. When combined with a nonrigid registration algorithm that can leverage partial matches, this approach allows efficient tracking of all cells with substantially less manual intervention. Further work is needed to integrate this into previous registration pipelines.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Hang Deng,James Yu, andVivek Venkatachalam
"Neuron tracking in C. elegans through automated anchor neuron localization and segmentation", Proc. SPIE 12857, Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences, 128570H (13 March 2024); https://doi.org/10.1117/12.3001982
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Hang Deng, James Yu, Vivek Venkatachalam, "Neuron tracking in C. elegans through automated anchor neuron localization and segmentation," Proc. SPIE 12857, Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences, 128570H (13 March 2024); https://doi.org/10.1117/12.3001982