Abstract

Optical coherence tomography (OCT) images are commonly affected by sidelobe artifacts due to spectral non-uniformity and spectral leakage. Conventional frequency domain spectral shaping methods widen the mainlobe and compromise axial resolution. While image-domain deconvolution techniques can address the trade-off between axial resolution and artifact suppression, their reconstruction quality relies on accurate measurement or estimation of system point spread function (PSF). Inaccurate PSF estimation leads to loss of details in the reconstructed images. In this Letter, we introduce multi-shaping sparse-continuous reconstruction (MSSCR) for an OCT image, a novel, to the best of our knowledge, framework that combines spectral multi-shaping and iterative image reconstruction with sparse-continuous priors. The MSSCR achieves sidelobe suppression without requiring any PSF measurement or estimation and effectively preserving the axial resolution. The experimental results demonstrate that the MSSCR achieves sidelobe suppression of more than 8 dB. We believe that the MSSCR holds potential for addressing sidelobe artifacts in OCT.

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