Are model-based tools still relevant for bioimage analysis?

New methods for background estimation and denoising fight back

• Mauro Silberberg
• maurosilber@df.uba.ar
• maurosilber@gmail.com
• Hernán E. Grecco

Poster

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Slides

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Articles

• SMO - Silberberg and Grecco (2023) - PDF - supp. - GitHub - Twitter

  Robust estimation of the background distribution.

• binlets - Silberberg and Grecco (2024) - PDF - GitHub - Twitter 1 & 2

  Adaptive binning for multichannel signals.

• pawFLIM - Silberberg and Grecco (2017) - PDF - supp. - GitHub - Twitter

  Application of binlets to Fluorescence Lifetime Imaging Micropscopy.

References

Silberberg, Mauro, and Hernán E. Grecco. 2017. “pawFLIM: Reducing Bias and Uncertainty to Enable Lower Photon Count in FLIM Experiments.” Methods and Applications in Fluorescence 5 (2): 024016. https://doi.org/10.1088/2050-6120/aa72ab.

———. 2023. “Robust and Unbiased Estimation of the Background Distribution for Automated Quantitative Imaging.” Journal of the Optical Society of America A 40 (4): C8. https://doi.org/10.1364/JOSAA.477468.

———. 2024. “Binlets: Data Fusion-Aware Denoising Enables Accurate and Unbiased Quantification of Multichannel Signals.” Information Fusion 101 (January): 101999. https://doi.org/10.1016/j.inffus.2023.101999.