Extended Data Fig. 6: Fine tuning DeepInterpolation models with an L2 loss yields better reconstruction when photon count is very low. | Nature Methods

Extended Data Fig. 6: Fine tuning DeepInterpolation models with an L2 loss yields better reconstruction when photon count is very low.

From: Removing independent noise in systems neuroscience data using DeepInterpolation

Extended Data Fig. 6

(a) Comparison of an example image in a two-photon movie showing VIP cells expressed GCaMP6s in Raw data, after DeepInterpolation with a broadly trained model (Ai93), after DeepInterpolation with a model trained on VIP data with an L1 loss and after DeepInterpolation with a model trained on VIP data with an L2 loss. Scale bar is 100 𝜇m. (b) Simulation of reconstruction error when using either the L1 loss or the L2 loss for various levels of photon count and corrupted frames.

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