%0 Conference Paper
%A Welker, Simon
%A Peer, Tal
%A Chapman, Henry N.
%A Gerkmann, Timo
%T Deep Iterative Phase Retrieval for Ptychography
%C Piscataway, NJ
%I IEEE
%M PUBDB-2023-00144
%@ 978-1-6654-0540-9
%P 1591-1595
%D 2022
%Z Literaturangaben;
%< [Ebook] 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing : proceedings : 7-13 May 2022, virtual (all paper presentations) : 22-27 May 2022, main venue: Marina Bay Sands Expo & Convention Center, Singapore, satellite venue: Shenzhen, China / sponsored by: the Institute of Electrical and Electronics Engineers, Signal Processing Society , Piscataway, NJ : IEEE, 2022,
%X One of the most prominent challenges in the field of diffractive imaging is the phase retrieval (PR) problem: In order to reconstruct an object from its diffraction pattern, the inverse Fourier transform must be computed. This is only possible given the full complex-valued diffraction data, i.e. magnitude and phase. However, in diffractive imaging, generally only magnitudes can be directly measured while the phase needs to be estimated. In this work we specifically consider ptychography, a sub-field of diffractive imaging, where objects arereconstructed from multiple overlapping diffraction images. We pro- pose an augmentation of existing iterative phase retrieval algorithms with a neural network designed for refining the result of each iteration. For this purpose we adapt and extend a recently proposed architecture from the speech processing field. Evaluation results show the proposed approach delivers improved convergence rates in terms of both iteration count and algorithm runtime.
%B ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing 
%C 23 May 2022 - 27 May 2022, Singapore (Singapore)
Y2 23 May 2022 - 27 May 2022
M2 Singapore, Singapore
%F PUB:(DE-HGF)8 ; PUB:(DE-HGF)7
%9 Contribution to a conference proceedingsContribution to a book
%R 10.1109/ICASSP43922.2022.9746811
%U https://bib-pubdb1.desy.de/record/491435