Ge X, Chen S, Lin K et al. Deblurring, artifact-free optical coherence tomography with deconvolution-random phase modulation. Opto-Electron Sci 3, 230020 (2024). doi: 10.29026/oes.2024.230020
Citation: Ge X, Chen S, Lin K et al. Deblurring, artifact-free optical coherence tomography with deconvolution-random phase modulation. Opto-Electron Sci 3, 230020 (2024). doi: 10.29026/oes.2024.230020

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Deblurring, artifact-free optical coherence tomography with deconvolution-random phase modulation

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  • Deconvolution is a commonly employed technique for enhancing image quality in optical imaging methods. Unfortunately, its application in optical coherence tomography (OCT) is often hindered by sensitivity to noise, which leads to additive ringing artifacts. These artifacts considerably degrade the quality of deconvolved images, thereby limiting its effectiveness in OCT imaging. In this study, we propose a framework that integrates numerical random phase masks into the deconvolution process, effectively eliminating these artifacts and enhancing image clarity. The optimized joint operation of an iterative Richardson-Lucy deconvolution and numerical synthesis of random phase masks (RPM), termed as Deconv-RPM, enables a 2.5-fold reduction in full width at half-maximum (FWHM). We demonstrate that the Deconv-RPM method significantly enhances image clarity, allowing for the discernment of previously unresolved cellular-level details in nonkeratinized epithelial cells ex vivo and moving blood cells in vivo.
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  • [1] Liu LB, Gardecki JA, Nadkarni SK et al. Imaging the subcellular structure of human coronary atherosclerosis using micro–optical coherence tomography. Nat Med 17, 1010–1014 (2011). doi: 10.1038/nm.2409

    CrossRef Google Scholar

    [2] Liu XY, Chen S, Cui DY et al. Spectral estimation optical coherence tomography for axial super-resolution. Opt Express 23, 26521–26532 (2015). doi: 10.1364/OE.23.026521

    CrossRef Google Scholar

    [3] Shemonski ND, South FA, Liu YZ et al. Computational high-resolution optical imaging of the living human retina. Nat Photonics 9, 440–443 (2015). doi: 10.1038/nphoton.2015.102

    CrossRef Google Scholar

    [4] Zhou KC, Qian RB, Degan S et al. Optical coherence refraction tomography. Nat Photonics 13, 794–802 (2019). doi: 10.1038/s41566-019-0508-1

    CrossRef Google Scholar

    [5] Liba O, Lew MD, SoRelle ED et al. Speckle-modulating optical coherence tomography in living mice and humans. Nat Commun 8, 15845 (2017). doi: 10.1038/ncomms15845

    CrossRef Google Scholar

    [6] Kang JQ, Zhu R, Sun YX et al. Pencil-beam scanning catheter for intracoronary optical coherence tomography. Opto-Electron Adv 5, 200050 (2022). doi: 10.29026/oea.2022.200050

    CrossRef Google Scholar

    [7] Ginner L, Kumar A, Fechtig D et al. Noniterative digital aberration correction for cellular resolution retinal optical coherence tomography in vivo. Optica 4, 924–931 (2017). doi: 10.1364/OPTICA.4.000924

    CrossRef Google Scholar

    [8] Ralston TS, Marks DL, Carney PS et al. Interferometric synthetic aperture microscopy. Nat Phys 3, 129–134 (2007). doi: 10.1038/nphys514

    CrossRef Google Scholar

    [9] Hillmann D, Spahr H, Hain C et al. Aberration-free volumetric high-speed imaging of in vivo retina. Sci Rep 6, 35209 (2016). doi: 10.1038/srep35209

    CrossRef Google Scholar

    [10] Adie SG, Graf BW, Ahmad A et al. Computational adaptive optics for broadband optical interferometric tomography of biological tissue. Proc Natl Acad Sci USA 109, 7175–7180 (2012). doi: 10.1073/pnas.1121193109

    CrossRef Google Scholar

    [11] Adie SG, Shemonski ND, Graf BW et al. Guide-star-based computational adaptive optics for broadband interferometric tomography. Appl Phys Lett 101, 221117 (2012). doi: 10.1063/1.4768778

    CrossRef Google Scholar

    [12] Yu LF, Rao B, Zhang J et al. Improved lateral resolution in optical coherence tomography by digital focusing using two-dimensional numerical diffraction method. Opt Express 15, 7634–7641 (2007). doi: 10.1364/OE.15.007634

    CrossRef Google Scholar

    [13] Yasuno Y, Sugisaka JI, Sando Y et al. Non-iterative numerical method for laterally superresolving Fourier domain optical coherence tomography. Opt Express 14, 1006–1020 (2006). doi: 10.1364/OE.14.001006

    CrossRef Google Scholar

    [14] Ralston TS, Marks DL, Kamalabadi F et al. Deconvolution methods for mitigation of transverse blurring in optical coherence tomography. IEEE Trans Image Process 14, 1254–1264 (2005). doi: 10.1109/TIP.2005.852469

    CrossRef Google Scholar

    [15] Woolliams PD, Ferguson RA, Hart C et al. Spatially deconvolved optical coherence tomography. Appl Opt 49, 2014–2021 (2010). doi: 10.1364/AO.49.002014

    CrossRef Google Scholar

    [16] Liu GZ, Yousefi S, Zhi ZW et al. Automatic estimation of point-spread-function for deconvoluting out-of-focus optical coherence tomographic images using information entropy-based approach. Opt Express 19, 18135–18148 (2011). doi: 10.1364/OE.19.018135

    CrossRef Google Scholar

    [17] Hojjatoleslami SA, Avanaki MRN, Podoleanu AG. Image quality improvement in optical coherence tomography using Lucy–Richardson deconvolution algorithm. Appl Opt 52, 5663–5670 (2013). doi: 10.1364/AO.52.005663

    CrossRef Google Scholar

    [18] Liu YH, Liang YM, Mu GG et al. Deconvolution methods for image deblurring in optical coherence tomography. J Opt Soc Am A 26, 72–77 (2009). doi: 10.1364/JOSAA.26.000072

    CrossRef Google Scholar

    [19] Liu YZ, South FA, Xu Y et al. Computational optical coherence tomography [Invited]. Biomed Opt Express 8, 1549–1574 (2017). doi: 10.1364/BOE.8.001549

    CrossRef Google Scholar

    [20] van Kempen GMP, van Vliet LJ. Background estimation in nonlinear image restoration. J Opt Soc Am A 17, 425–433 (2000). doi: 10.1364/JOSAA.17.000425

    CrossRef Google Scholar

    [21] Dey N, Blanc‐Feraud L, Zimmer C et al. Richardson–Lucy algorithm with total variation regularization for 3D confocal microscope deconvolution. Microsc Res Tech 69, 260–266 (2006). doi: 10.1002/jemt.20294

    CrossRef Google Scholar

    [22] Bianco V, Paturzo M, Memmolo P et al. Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography. Opt Lett 38, 619–621 (2013). doi: 10.1364/OL.38.000619

    CrossRef Google Scholar

    [23] Bianco V, Memmolo P, Paturzo M et al. Quasi noise-free digital holography. Light Sci Appl 5, e16142 (2016). doi: 10.1038/lsa.2016.142

    CrossRef Google Scholar

    [24] Bianco V, Memmolo P, Leo M et al. Strategies for reducing speckle noise in digital holography. Light Sci Appl 7, 48 (2018). doi: 10.1038/s41377-018-0050-9

    CrossRef Google Scholar

    [25] Anand V, Han ML, Maksimovic J et al. Single-shot mid-infrared incoherent holography using Lucy-Richardson-Rosen algorithm. Opto-Electron Sci 1, 210006 (2022). doi: 10.29026/oes.2022.210006

    CrossRef Google Scholar

    [26] Ozcan A, Bilenca A, Desjardins AE et al. Speckle reduction in optical coherence tomography images using digital filtering. J Opt Soc Am A 24, 1901–1910 (2007).

    Google Scholar

    [27] Chen S, Ge X, Liu XY et al. Understanding optical reflectance contrast for real‐time characterization of epithelial precursor lesions. Bioeng Transl Med 4, e10137 (2019). doi: 10.1002/btm2.10137

    CrossRef Google Scholar

    [28] Ge X, Tang HY, Wang XH et al. Geometry-dependent spectroscopic contrast in deep tissues. iScience 19, 965–975 (2019). doi: 10.1016/j.isci.2019.08.046

    CrossRef Google Scholar

    [29] Ma XH, Wang AT, Ma FH et al. Speckle reduction using phase plate array and lens array. Opto-Electron Adv 3, 190036 (2020).

    Google Scholar

    [30] Bashkansky M, Reintjes J. Statistics and reduction of speckle in optical coherence tomography. Opt Lett 25, 545–547 (2000). doi: 10.1364/OL.25.000545

    CrossRef Google Scholar

    [31] Schmitt JM, Xiang SH, Yung KM. Speckle in optical coherence tomography. J Biomed Opt 4, 95–105 (1999). doi: 10.1117/1.429925

    CrossRef Google Scholar

    [32] Guizar-Sicairos M, Thurman ST, Fienup JR. Efficient subpixel image registration algorithms. Opt Lett 33, 156–158 (2008). doi: 10.1364/OL.33.000156

    CrossRef Google Scholar

    [33] Refregier P, Javidi B. Optical image encryption based on input plane and Fourier plane random encoding. Opt Lett 20, 767–769 (1995). doi: 10.1364/OL.20.000767

    CrossRef Google Scholar

    [34] Bo E, Luo YM, Chen S et al. Depth-of-focus extension in optical coherence tomography via multiple aperture synthesis. Optica 4, 701–706 (2017). doi: 10.1364/OPTICA.4.000701

    CrossRef Google Scholar

    [35] Kumar A, Drexler W, Leitgeb RA. Subaperture correlation based digital adaptive optics for full field optical coherence tomography. Opt Express 21, 10850–10866 (2013). doi: 10.1364/OE.21.010850

    CrossRef Google Scholar

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