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Deep-Learning for phase unwrapping in Lens-Free imaging
Author(s): L. Hervé; C. Allier; O. Cioni; F. Navarro; M. Menneteau; S. Morales
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Paper 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.

Paper Details

Date Published: 22 July 2019
PDF: 3 pages
Proc. SPIE 11076, Advances in Microscopic Imaging II, 1107610 (22 July 2019); doi: 10.1117/12.2527004
Show Author Affiliations
L. Hervé, Univ. Grenoble Aples, CEA, LETI (France)
C. Allier, Univ. Grenoble Alpes, CEA, LETI (France)
O. Cioni, Univ. Grenoble Alpes, CEA, LETI (France)
F. Navarro, Univ. Grenoble Alpes, CEA, LETI (France)
M. Menneteau, Univ. Grenoble Alpes, CEA, LETI (France)
S. Morales, Univ. Grenoble Alpes, CEA, LETI (France)


Published in SPIE Proceedings Vol. 11076:
Advances in Microscopic Imaging II
Emmanuel Beaurepaire; Francesco Saverio Pavone; Peter T. C. So, Editor(s)

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