Ge-Lang Hu

DeepMoCo: graph neural network-based adaptive correction for motion artifacts in fluorescence microscopy

DeepMoCo is proposed, an innovative deep learning-based framework that integrates a graph neural network (GNN) to establish spatiotemporal feature correlations between biological motion patterns and imaging artifacts and presents a robust and universal solution for high-precision in vivo fluorescence imaging studies.