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Phase Retrieval Method for Phase-shifting Interferometry with Machine Learning

Published: 25 May 2020 Publication History

Abstract

Phase contrast imaging attracts attention in the biomedical field thanks to higher contrast than absorption contrast. However, the phase retrieval for phase-shifting interferometry (PSI) often involves the problems, e.g., the noise, stepping error and phase wrapping. In the conventional way, each issue had to be addressed individually. In this paper, we propose the machine learning based method, which uses the neural network and learns features in an end-to-end manner. The proposed method can resolve the noise, stepping error artifacts and phase wrapping, simultaneously. The results are shown by numerical simulation.

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    ICVISP 2019: Proceedings of the 3rd International Conference on Vision, Image and Signal Processing
    August 2019
    584 pages
    ISBN:9781450376259
    DOI:10.1145/3387168
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 25 May 2020

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    Author Tags

    1. Machine Learning
    2. Neural Network
    3. Phase Retrieval
    4. Phase Shifting Interferometry

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    ICVISP 2019 Paper Acceptance Rate 126 of 277 submissions, 45%;
    Overall Acceptance Rate 186 of 424 submissions, 44%

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