Experimental validation of an optimized signal processing method to handle non-linearity in swept-source optical...

Area of Science:

• Optical Engineering
• Biomedical Imaging
• Signal Processing

Background:

• Swept-source optical coherence tomography (SS-OCT) systems often utilize laser sources exhibiting non-linearity in wavenumber space.
• This non-linearity complicates data processing and can degrade image quality in SS-OCT.
• Efficient signal processing is crucial for accurate and high-resolution SS-OCT imaging.

Purpose of the Study:

• To evaluate and compare various signal processing techniques for correcting wavenumber non-linearity in SS-OCT.
• To identify the most efficient method that maintains high image quality while minimizing computational cost.

Main Methods:

• Comparison of non-uniform discrete Fourier transforms (NDFT) using Vandermonde matrix or Lomb periodogram.
• Evaluation of resampling techniques including linear and spline interpolation prior to fast Fourier transform (FFT).
• Assessment of resampling with convolution prior to FFT, specifically optimizing the Kaiser-Bessel window function.

Main Results:

• The convolution method followed by FFT demonstrated superior efficiency compared to NDFT and interpolation-based resampling.
• Optimizing the Kaiser-Bessel window for convolution allowed for a minimal fractional oversampling factor (1-2).
• This optimized convolution approach significantly reduced computational time while preserving excellent SS-OCT image quality.

Conclusions:

• Resampling with convolution prior to FFT is the most effective signal processing strategy for SS-OCT.
• This method efficiently addresses wavenumber non-linearity, leading to improved computational performance and image fidelity.
• The findings provide a practical guideline for optimizing SS-OCT data processing.