Abstract
Astrocytes regulate neuronal information processing through a variety of spatio-temporal calcium signals. Recent advances in calcium imaging have started to shine light on astrocytic activity, but the complexity and size of the recorded data strongly call for more advanced computational analysis tools. Their development is currently hindered by the lack of reliable, labeled annotations that are essential for the evaluation of algorithms and the training of learning-based methods. To solve this labeling problem, we have designed a generator of 2D/3D lattice light sheet microscopy (LLSM) sequences which realistically depict the calcium dynamics of astrocytes. By closely modeling calcium kinetics in real astrocytic ramifications, the generated datasets open the door for the deployment of convolutional neural networks in LLSM.
Demos 2D+time
Source real data: M. Arizono, M. Ducros, U. V. Nägerl, Interdisciplinary Institute for Neuroscience, Bordeaux.
Demos 3D+time
Source real data: M. Arizono, M. Ducros, U. V. Nägerl, Interdisciplinary Institute for Neuroscience, Bordeaux.
