| Issue |
EPJ Web Conf.
Volume 335, 2025
EOS Annual Meeting (EOSAM 2025)
|
|
|---|---|---|
| Article Number | 01006 | |
| Number of page(s) | 2 | |
| Section | Face2Phase (F2P) | |
| DOI | https://doi.org/10.1051/epjconf/202533501006 | |
| Published online | 22 September 2025 | |
https://doi.org/10.1051/epjconf/202533501006
Event-based reconstructions in Computational Microscopy
1 Advanced Research Center for Nanolithography (ARCNL), Science Park 106, 1098 XG Amsterdam, The Netherlands
2 Imaging Physics, Faculty of Applied Sciences, Technische Universiteit Delft, Lorentzweg 1, 2600 GA, Delft, the Netherlands
3 Debye Institute for Nanomaterials Science and Center for Extreme Matter and Emergent Phenomena, Utrecht University, 3584 CC Utrecht, The Netherlands
4 Department of Physics and Astronomy, Vrije Universiteit, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands
* e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 22 September 2025
Abstract
We present a maximum-likelihood estimation (MLE) framework tailored to event-driven detectors to perform computational image reconstruction and phase retrieval. Using Poissonian photon statistics, we built an event-based loss function that maximizes the probability of having the set of events and non-events given the initial parameters. Our loss function can be utilized in both optical and electron ptychography. We demonstrate experimental reconstructions using data acquired with a Timepix3 detector.
© The Authors, published by EDP Sciences, 2025
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