Time-Dependent Entropy Deconvolution

About

This program deconvolves microscopy images. The input can either be a 2D single image or a 2D time series. The corresponding publication is published as a preprint in [1]. The 2D-only version is based on [2]. For the deconvolution of a time series, a regularizer in time domain was added. The point spread function can either be given as image input or calculated analytically with the relevant parameters.

Usage

  1. Download the Code and install the necessary Python packages, see Setup
  2. Enter parameters in parameters.json file, see Usage
  3. Run python main.py

References

[1] L. Woelk, S. A. Kannabiran, V. Brock, Ch. E. Gee, Ch. Lohr, A. H. Guse, B. Diercks, and R. Werner. 2021. "Time-Dependent Image Restoration of Low-SNR Live Cell Ca2+ Fluorescence Microscopy Data". bioRxiv 2021.10.05.462864. https://doi.org/10.1101/2021.10.05.462864.

[2] Arigovindan, Muthuvel, Jennifer C. Fung, Daniel Elnatan, Vito Mennella, Yee-Hung Mark Chan, Michael Pollard, Eric Branlund, John W. Sedat, und David A. Agard. 2013. „High-Resolution Restoration of 3D Structures from Widefield Images with Extreme Low Signal-to-Noise-Ratio". Proceedings of the National Academy of Sciences 110 (43): 17344–49. https://doi.org/10.1073/pnas.1315675110.