Code and Data for 'Fabrication and testing of lensed fiber optic probes for distance sensing using common path low coherence interferometry'

This repository contains code and data to support the paper:Fabrication and testing of lensed fiber optic probes for distance sensing using common path low coherence interferometryRadu-Florin Stancu,¹ Michael Hughes,¹Taylor Sanderson,¹Manuel Marques,¹ Lyndon da Cruz,² Christos Bergeles,³ and Adrian Podoleanu¹Applied Optics Group, University of KentMoorfields Eye Hospital, LondonKing’s College London, Robotics and Vision in Medicine Lab, School of Biomedical Engineering & Imaging SciencesContents--------1. ModellingPython code to demonstrate use of Eqn 1 from paper to model fiber probes using coreless and GRIN fiber. 'model.py' contains the function 'grin_model' which models the working distance and focused spot FWHM base on the length of NCF and GRIN fibre. 'model_example_1.py' and 'mode_example_2.py' provide examples of how to use the function to model a particular probe and to explore the parameter space, respectively.2. SputteringRaw data and code to produce Fig. 2 from paper, showing effect of sputtering time on reflectivity.3. Spot AnalysisCode and example data for analysis of focal spots from fiber probes. 'Spot_utilities.py' contains several functions that are useful to help with the analysis, and 'spot_analysis.py' provides an example of how to use them, generating Fig 4 from the paper. The 'data' folder contains a set of spot images as the tip of the probe was moved either side of focus in steps of 50 microns. File names are the distance from the estimated focus in microns.4. A ScansExample A-scans in the 'data' folder were used to generate Fig 6. from the paper. Code to generate the figure is in 'plot_a_scans.py'.5. Distance SensingCode and data to demonstrate extracting distance sensing data from A-scans and to generate Fig. 8 using the algorithm described in Fig. 7. Functions to generate distance measurements are in 'distance_sensing_utilities.py' and an example of how to use this on data in the 'data' folder is in 'distance_sensing_example.py', which generates Fig 8. Code to check axial resolution, as reported in the paper, is also included in this folder in 'resolution_measurement.py'.Running the code----------------Code was tested with Python 3.10.14Packages requirements (tested version shown):numpy 1.26.4matplotlib 3.8.4scipy 1.13.1opencv-python 4.9.0.80PIL 10.3.0