Deconvolution with fall-off compensated axial point spread function in spectral domain optical coherence tomography

Abstract A deconvolution method for image enhancement suitable for spectral domain optical coherence tomography (SD-OCT) is proposed. The method includes Wiener filtering for spectral deconvolution and successive homomorphic filtering for spatial deconvolution, aiming to minimize blurring effect of axial point spread function (PSF) and its depth dependence. Tunable factor in Wiener filtering is optimized for tradeoff between compensation ratio and signal-to-noise ratio (SNR). In vivo OCT imaging of a fresh shrimp is done and image reconstructions are performed. Comparing results demonstrates the proposed method suppresses the coherent noises in OCT image while compensating sensitivity fall-off with increased averaged SNR and recovers structural information at deep depths. Contrast-to-noise ratio (CNR) and averaged SNR in the reconstructed image based on the proposed method in contrast to those without deconvolution are improved by 3.4 dB and 4.6 dB, respectively.