Deep-learning for phase unwrapping in lens-free imaging

L. Hervé; C. Allier; O. Cioni; F. Navarro; M. Menneteau; S. Morales

doi:10.1117/12.2527004

22 July 2019 Deep-learning for phase unwrapping in lens-free imaging

L. Hervé, C. Allier, O. Cioni, F. Navarro, M. Menneteau, S. Morales

Proceedings Volume 11076, Advances in Microscopic Imaging II; 1107610 (2019) https://doi.org/10.1117/12.2527004
Event: European Conferences on Biomedical Optics, 2019, Munich, Germany

Abstract

Lens-Free microscopy aims at recovering an observed object such as cell cultures from its diffraction measurements. Diffraction acquisitions are processed with an inverse problem approach to recover optical path difference (OPD) images of the object. Phase unwrapping issue is solved here by using a convolutional neural network (CNN) trained on simulations. The procedure was applied successfully on a neuron cells culture video acquisition.

Citation Download Citation

L. Hervé, C. Allier, O. Cioni, F. Navarro, M. Menneteau, and S. Morales "Deep-learning for phase unwrapping in lens-free imaging", Proc. SPIE 11076, Advances in Microscopic Imaging II, 1107610 (22 July 2019); https://doi.org/10.1117/12.2527004

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