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Title: PtychoNet: Fast and High Quality Phase Retrieval for Ptychography

Abstract

Ptychography is a coherent diffractive imaging method that captures multiple diffraction patterns of a sample with a set of shifted localized illuminations (“probes”). The reconstruction problem, known as “phase retrieval”, is typically solved by iterative algorithms. In this paper, we propose PtychoNet, a deep learning based method to perform phase retrieval for ptychography in a non-iterative manner. We devise a generative network to encode a full ptychography scan, reverse the diffractions at each scanning point and compute the amplitude and phase of the object. We demonstrate successful reconstructions using PtychoNet as well as recovering fine features in the case of extreme sparse scanning where conventional iterative methods fail to give recognizable features.

Authors:
 [1]; ORCiD logo [2];  [3];  [2];  [1]
  1. Stony Brook Univ., NY (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States). Center for Functional Nanomaterials (CFN)
  3. Brookhaven National Lab. (BNL), Upton, NY (United States). National Synchrotron Light Source II (NSLS-II)
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1599580
Report Number(s):
BNL-213637-2020-FORE
DOE Contract Number:  
SC0012704
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Guan, Ziqiao, Tsai, Esther H., Huang, Xiaojing, Yager, Kevin G., and Qin, Hong. PtychoNet: Fast and High Quality Phase Retrieval for Ptychography. United States: N. p., 2019. Web. doi:10.2172/1599580.
Guan, Ziqiao, Tsai, Esther H., Huang, Xiaojing, Yager, Kevin G., & Qin, Hong. PtychoNet: Fast and High Quality Phase Retrieval for Ptychography. United States. https://doi.org/10.2172/1599580
Guan, Ziqiao, Tsai, Esther H., Huang, Xiaojing, Yager, Kevin G., and Qin, Hong. 2019. "PtychoNet: Fast and High Quality Phase Retrieval for Ptychography". United States. https://doi.org/10.2172/1599580. https://www.osti.gov/servlets/purl/1599580.
@article{osti_1599580,
title = {PtychoNet: Fast and High Quality Phase Retrieval for Ptychography},
author = {Guan, Ziqiao and Tsai, Esther H. and Huang, Xiaojing and Yager, Kevin G. and Qin, Hong},
abstractNote = {Ptychography is a coherent diffractive imaging method that captures multiple diffraction patterns of a sample with a set of shifted localized illuminations (“probes”). The reconstruction problem, known as “phase retrieval”, is typically solved by iterative algorithms. In this paper, we propose PtychoNet, a deep learning based method to perform phase retrieval for ptychography in a non-iterative manner. We devise a generative network to encode a full ptychography scan, reverse the diffractions at each scanning point and compute the amplitude and phase of the object. We demonstrate successful reconstructions using PtychoNet as well as recovering fine features in the case of extreme sparse scanning where conventional iterative methods fail to give recognizable features.},
doi = {10.2172/1599580},
url = {https://www.osti.gov/biblio/1599580}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {9}
}