Yuanlong Zhang

The paper introduces DeepWonder3D, a pipeline for rapid and robust 3D neuronal extraction from multi-view projections, achieving high fidelity and efficiency in calcium dynamics analysis.

This paper introduces an unsupervised deep-learning method for multi-animal tracking that performs well in challenging conditions without requiring human annotations.

This paper introduces a miniaturized mesoscope (SOMM) for high-resolution calcium imaging in freely moving mice, achieving widefield, cellular resolution with robustness against motion artifacts.

The paper introduces a mesoscale light field imaging system for high-speed volumetric calcium imaging of neuronal activity in mouse cortex.

This paper introduces DeepCAD, a self-supervised learning method to enhance calcium imaging by reducing noise and improving SNR, leading to better neuron extraction and spike inference.

This paper introduces ED-LTFM to overcome tissue scattering in wide-field deep imaging, demonstrating improved imaging depth in mouse brain in vivo.