Experimental validation of an optimized signal processing method to handle non-linearity in swept-source optical coherence tomography
Related Experiment Video
Updated: Jun 11, 2026

Multimodal Volumetric Retinal Imaging by Oblique Scanning Laser Ophthalmoscopy (oSLO) and Optical Coherence Tomography (OCT)
Published on: August 4, 2018
Sébastien Vergnole1, Daniel Lévesque, Guy Lamouche
1Industrial Materials Institute, National Research Council Canada, Boucherville, QC, J4B 6Y4, Canada. Sebastien.Vergnole@cnrc-nrc.gc.ca
Abstract:
We evaluate various signal processing methods to handle the non-linearity in wavenumber space exhibited by most laser sources for swept-source optical coherence tomography. The following methods are compared for the same set of experimental data: non-uniform discrete Fourier transforms with Vandermonde matrix or with Lomb periodogram, resampling with linear interpolation or spline interpolation prior to fast-Fourier transform (FFT), and resampling with convolution prior to FFT. By selecting an optimized Kaiser-Bessel window to perform the convolution, we show that convolution followed by FFT is the most efficient method. It allows small fractional oversampling factor between 1 and 2, thus a minimal computational time, while retaining an excellent image quality.
Related Concept Videos
Linear Approximation in Time Domain
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length, the...
Computed Tomography
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
Imaging Biological Samples with Optical Microscopy
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
Linear Approximation in Frequency Domain
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.

