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Robust real-time imaging through flexible multimode fibers
by
Altmann, Yoann
, Padgett, Miles J.
, Abdulaziz, Abdullah
, Mekhail, Simon Peter
, McLaughlin, Stephen
in
639/624/1107/510
/ 639/705/1042
/ 639/766/930/2735
/ Deep learning
/ Endoscopes
/ Fibers
/ Humanities and Social Sciences
/ Light
/ Measurement techniques
/ multidisciplinary
/ Science
/ Science (multidisciplinary)
2023
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Robust real-time imaging through flexible multimode fibers
by
Altmann, Yoann
, Padgett, Miles J.
, Abdulaziz, Abdullah
, Mekhail, Simon Peter
, McLaughlin, Stephen
in
639/624/1107/510
/ 639/705/1042
/ 639/766/930/2735
/ Deep learning
/ Endoscopes
/ Fibers
/ Humanities and Social Sciences
/ Light
/ Measurement techniques
/ multidisciplinary
/ Science
/ Science (multidisciplinary)
2023
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Robust real-time imaging through flexible multimode fibers
by
Altmann, Yoann
, Padgett, Miles J.
, Abdulaziz, Abdullah
, Mekhail, Simon Peter
, McLaughlin, Stephen
in
639/624/1107/510
/ 639/705/1042
/ 639/766/930/2735
/ Deep learning
/ Endoscopes
/ Fibers
/ Humanities and Social Sciences
/ Light
/ Measurement techniques
/ multidisciplinary
/ Science
/ Science (multidisciplinary)
2023
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Robust real-time imaging through flexible multimode fibers
Journal Article
Robust real-time imaging through flexible multimode fibers
2023
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Overview
Conventional endoscopes comprise a bundle of optical fibers, associating one fiber for each pixel in the image. In principle, this can be reduced to a single multimode optical fiber (MMF), the width of a human hair, with one fiber spatial-mode per image pixel. However, images transmitted through a MMF emerge as unrecognizable speckle patterns due to dispersion and coupling between the spatial modes of the fiber. Furthermore, speckle patterns change as the fiber undergoes bending, making the use of MMFs in flexible imaging applications even more complicated. In this paper, we propose a real-time imaging system using flexible MMFs, but which is robust to bending. Our approach does not require access or feedback signal from the distal end of the fiber during imaging. We leverage a variational autoencoder to reconstruct and classify images from the speckles and show that these images can still be recovered when the bend configuration of the fiber is changed to one that was not part of the training set. We utilize a MMF 300 mm long with a 62.5 μm core for imaging
10
×
10
cm objects placed approximately at 20 cm from the fiber and the system can deal with a change in fiber bend of 50
∘
and range of movement of 8 cm.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
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