Efficient and flexible approach to ptychography using an optimization framework based on automatic differentiation
Posted on 08.01.2021 - 21:46
Ptychography is a lensless imaging method that allows for wavefront sensing and phase-sensitive microscopy from a set of diffraction patterns. Recently, it has been shown that the optimization task in ptychography can be achieved via automatic differentiation (AD). Here, we propose an open-access AD-based framework implemented with TensorFlow, a popular machine learning library. Using simulations, we show that our AD-based framework performs comparably to a state-of-the-art implementation of the momentum-accelerated ptychographic iterative engine (mPIE) in terms of reconstruction speed and quality. AD-based approaches provide great flexibility, as we demonstrate by setting the reconstruction distance as a trainable parameter. Lastly, we experimentally demonstrate that our framework faithfully reconstructs a biological specimen.
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Seifert, Jacob; Bouchet, Dorian; Loetgering, Lars; Mosk, Allard (2021): Efficient and flexible approach to ptychography using an optimization framework based on automatic differentiation. The Optical Society. Collection. https://doi.org/10.6084/m9.figshare.c.5133590.v2
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