13 March 2017 A spatially-variant deconvolution method based on total variation for optical coherence tomography images
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Abstract
Optical Coherence Tomography (OCT) has a great potential to elicit clinically useful information from tissues due to its high axial and transversal resolution. In practice, an OCT setup cannot reach to its theoretical resolution due to imperfections of its components, which make its images blurry. The blurriness is different alongside regions of image; thus, they cannot be modeled by a unique point spread function (PSF). In this paper, we investigate the use of solid phantoms to estimate the PSF of each sub-region of imaging system. We then utilize Lucy-Richardson, Hybr and total variation (TV) based iterative deconvolution methods for mitigating occurred spatially variant blurriness. It is shown that the TV based method will suppress the so-called speckle noise in OCT images better than the two other approaches. The performance of proposed algorithm is tested on various samples, including several skin tissues besides the test image blurred with synthetic PSF-map, demonstrating qualitatively and quantitatively the advantage of TV based deconvolution method using spatially-variant PSF for enhancing image quality.
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Mohammad Almasganj, Saba Adabi, Emad Fatemizadeh, Qiuyun Xu, Hamid Sadeghi, Steven Daveluy, Mohammadreza Nasiriavanaki, "A spatially-variant deconvolution method based on total variation for optical coherence tomography images", Proc. SPIE 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1013725 (13 March 2017); doi: 10.1117/12.2255557; https://doi.org/10.1117/12.2255557
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