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Coherent Imaging Through Multicore Fibres With Applications in Endoscopy
Imaging through optical fibres has recently emerged as a promising method of micro-scale optical imaging within a hair-thin form factor. This has significant applications in endoscopy and may enable minimally invasive imaging deep within live tissue for improved diagnosis of disease. Multi-mode fibr...
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Published in: | Journal of lightwave technology 2019-11, Vol.37 (22), p.5733-5745 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Imaging through optical fibres has recently emerged as a promising method of micro-scale optical imaging within a hair-thin form factor. This has significant applications in endoscopy and may enable minimally invasive imaging deep within live tissue for improved diagnosis of disease. Multi-mode fibres (MMF) are the most common choice because of their high resolution but multicore fibres (MCF) offer a number of advantages such as widespread clinical use, ability to form approximate images without correction and an inherently sparse transmission matrix (TM) enabling simple and fast characterisation. We present a novel experimental investigation into properties of MCF important for imaging, specifically: a new method to upsample and downsample measured TMs with minimal information loss, the first experimental measurement of MCF spatial eigenmodes, a novel statistical treatment of behaviour under bending based on a wireless fading model, and an experimental observation of TM drift due to self-heating effects and discussion of how to compensate this. We next present practical techniques for imaging through MCFs, including alignment, how to parallelise TM characterisation measurements to improve speed and how to use non-interferometric phase and polarisation recovery for improved stability. Finally, we present two recent applications of MCF imaging: polarimetric imaging using a robust Bayesian inference approach, and entropic imaging for imaging early-stage tumours. |
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ISSN: | 0733-8724 1558-2213 |
DOI: | 10.1109/JLT.2019.2932901 |