Spectral estimation optical coherence tomography for axial super-resolution (Conference Presentation)

The sample depth reflectivity profile of Fourier domain optical coherence tomography (FD-OCT) is estimated from the inverse Fourier transform of the spectral interference signals (interferograms). As a result, the axial resolution is fundamentally limited by the coherence length of the light source. We demonstrate an axial resolution improvement method by using the autoregressive spectral estimation technique to instead of the inverse Fourier transform to analyze the spectral interferograms, which is named as spectral estimation OCT (SE-OCT). SE-OCT improves the axial resolution by a factor of up to 4.7 compared with the corresponding FD-OCT. Furthermore, SE-OCT provides a complete sidelobe suppression in the point-spread function. Using phantoms such as an air wedge and micro particles, we prove the ability of resolution improvement. To test SE-OCT for real biological tissue, we image the rat cornea and demonstrate that SE-OCT enables clear identification of corneal endothelium anatomical details ex vivo. We also find that the performance of SE-OCT is depended on SNR of the feature object. To evaluate the potential usage and define the application scope of SE-OCT, we further investigate the property of SNR dependence and the artifacts that may be caused. We find SE-OCT may be uniquely suited for viewing high SNR layer structures, such as the epithelium and endothelium in cornea, retina and aorta. Given that SE-OCT can be implemented in the FD-OCT devices easily, the new capabilities provided by SE-OCT are likely to offer immediate improvements to the diagnosis and management of diseases based on OCT imaging.