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Event-based reconstructions in Computational Microscopy
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Event-based reconstructions in Computational Microscopy
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Journal Article
Event-based reconstructions in Computational Microscopy
2025
Overview
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.
Publisher
EDP Sciences
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