Geometric deep learning of particle motion by MAGIK
… A new geometric deep learning method can reconstruct cellular and subcellular
trajectories and characterize mobility in microscopic imaging, for a broad range of challenging
scenarios. … In their recent publication in Nature Machine Intelligence, Pineda et al. describe
a powerful geometric deep learning approach, based on graph neural networks (GNNs), for
particle tracking and for the characterization of object motion without explicit tracking (Fig. 1). …
trajectories and characterize mobility in microscopic imaging, for a broad range of challenging
scenarios. … In their recent publication in Nature Machine Intelligence, Pineda et al. describe
a powerful geometric deep learning approach, based on graph neural networks (GNNs), for
particle tracking and for the characterization of object motion without explicit tracking (Fig. 1). …
A new geometric deep learning method can reconstruct cellular and subcellular trajectories and characterize mobility in microscopic imaging, for a broad range of challenging scenarios.
nature.com
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