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Reconstruction of optical vector-fields with applications in endoscopic imaging

Accepted version
Peer-reviewed

Type

Article

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Authors

Gordon, George SD 
Ramos, Alberto Gil CP 
Alcolea, Maria P 

Abstract

We introduce a framework for the reconstruction of the amplitude, phase and polarisation of an optical vector-field using measurements acquired by an imaging device characterised by an integral transform with an unknown spatially-variant kernel. By incorporating effective regularisation terms, this new approach is able to recover an optical vector-field with respect to an arbitrary representation system, which may be different from the one used for device calibration. In particular, it enables the recovery of an optical vector-field with respect to a Fourier basis, which is shown to yield indicative features of increased scattering associated with tissue abnormalities. We demonstrate the effectiveness of our approach using synthetic holographic images as well as biological tissue samples in an experimental setting where measurements of an optical vector-field are acquired by a multicore fibre (MCF) endoscope, and observe that indeed the recovered Fourier coefficients are useful in distinguishing healthy tissues from tumours in early stages of oesophageal cancer.

Description

Keywords

Algorithms, Animals, Endoscopy, Esophageal Neoplasms, Esophagus, Fourier Analysis, Holography, Humans, Image Interpretation, Computer-Assisted, Mice, Microscopy

Journal Title

IEEE Transactions on Medical Imaging

Conference Name

Journal ISSN

0278-0062
1558-254X

Volume Title

Publisher

IEEE
Sponsorship
Cancer Research UK (21102)
Engineering and Physical Sciences Research Council (EP/N014588/1)
Medical Research Council (MC_PC_12009)
Cancer Research UK (C20/A20976)
European Commission (655282)
Engineering and Physical Sciences Research Council (EP/R003599/1)
Cancer Research UK (24669)
Cancer Research Uk (None)
M. Gataric and S. E. Bohndiek were supported by an EPSRC grant EP/N014588/1 for the centre for Mathematical and Statistical Analysis of Multimodal Clinical Imaging. G. S. D. Gordon and S. E. Bohndiek received funding from CRUK (C47594/A16267, C14303/A17197, C47594/A21102) and a pump-priming award from the Cancer Research UK Cambridge Centre Early Detection Programme (A20976). The work of F. Renna was funded in part by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 655282 and in part by the FCT grant SFRH/BPD/118714/2016.