22 May 1997 Deconvolution and enhancement of optical coherence tomograms
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Subsurface images of biological tissue obtained by optical coherence tomography (OCT) lack of contrast and are corrupted by coherent noise. In this study we investigated model-based deconvolution methods designed for improving the quality of optical-coherence tomograms of living skin. The methods incorporate a priori information about the point-spread function of the imaging optics, as well as optical properties of the tissue. Deconvolution of the aberrated point-spread function was carried out by using CLEAN, an iterative point reconstruction method. A modification of the standard CLEAN algorithm based on a Wiener filter was made to reduce corrugation artifacts in images of densely packed clusters of scatterers. The algorithms were evaluated first on simulated one-dimensional data arrays and then applied to two- dimensional optical coherence tomograms of skin. Our results suggest that significant improvement in image contrast and resolution can be achieved with the deconvolution algorithm.
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Joseph M. Schmitt, Zhou Liang, "Deconvolution and enhancement of optical coherence tomograms", Proc. SPIE 2981, Coherence Domain Optical Methods in Biomedical Science and Clinical Applications, (22 May 1997); doi: 10.1117/12.274321; https://doi.org/10.1117/12.274321

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