[1] B. E. Bouma et al. Optical coherence tomography. Nat. Rev. Methods Primers, 2, 79(2022).

[2] M. J. Gora et al. Endoscopic optical coherence tomography: technologies and clinical applications. Biomed. Opt. Express, 8, 2405(2017).

[3] M.-Y. Fu et al. The progress of optical coherence tomography in industry applications. Adv. Dev. Instrum., 5, 0053(2024).

[4] V. B. Silva et al. Signal-carrying speckle in optical coherence tomography: a methodological review on biomedical applications. J. Biomed. Opt., 27, 030901(2022).

[5] A. Agrawal et al. Three-dimensional characterization of optical coherence tomography point spread functions with a nanoparticle-embedded phantom. Opt. Lett., 35, 2269(2010).

[6] J. Wang, B. Wohlberg, R. Adamson. Convolutional dictionary learning for blind deconvolution of optical coherence tomography images. Biomed. Opt. Express, 13, 1834(2022).

[7] B. Baumann et al. Signal averaging improves signal-to-noise in oct images: but which approach works best, and when?. Biomed. Opt. Express, 10, 5755(2019).

[8] M. Szkulmowski, M. Wojtkowski. Averaging techniques for OCT imaging. Opt Express, 21, 9757(2013).

[9] J. J. Rico-Jimenez et al. Real-time oct image denoising using a self-fusion neural network. Biomed. Opt. Express, 13, 1398(2022).

[10] J. Nienhaus et al. Live 4D-OCT denoising with self-supervised deep learning. Sci. Rep., 13, 5760(2023).

[11] B. Qiu et al. N2NSR-OCT: simultaneous denoising and super-resolution in optical coherence tomography images using semisupervised deep learning. J. Biophotonics, 14, e202000282(2021).

[12] A. Guo et al. Unsupervised denoising of optical coherence tomography images with nonlocal-generative adversarial network. IEEE Trans. Instrum. Meas., 70, 1(2020).

[13] Y. Li, Y. Fan, H. Liao. Self-supervised speckle noise reduction of optical coherence tomography without clean data. Biomed. Opt. Express, 13, 6357(2022).

[14] J. Liu et al. Future-proof imaging: computational imaging. Adv. Imaging, 1, 012001(2024).

[15] J. M. Schmitt, Z. Liang. Deconvolution and enhancement of optical coherence tomograms, 2981, 46(1997).

[16] J. M. Schmitt. Restoration of optical coherence images of living tissue using the clean algorithm. J. Biomed. Opt., 3, 66(1998).

[17] J. Högbom. Aperture synthesis with a non-regular distribution of interferometer baselines. Astron. Astrophys. Suppl. Ser., 15, 417(1974).

[18] T. S. Ralston et al. Deconvolution methods for mitigation of transverse blurring in optical coherence tomography. IEEE Trans. Image Process., 14, 1254(2005).

[19] Y. Liu et al. Deconvolution methods for image deblurring in optical coherence tomography. JOSA A, 26, 72(2009).

[20] S. Hojjatoleslami, M. Avanaki, A. G. Podoleanu. Image quality improvement in optical coherence tomography using lucy–richardson deconvolution algorithm. Appl. Opt., 52, 5663(2013).

[21] E. Bousi, C. Pitris. Axial resolution improvement by modulated deconvolution in fourier domain optical coherence tomography. J. Biomed. Opt., 17, 071307(2012).

[22] G. Liu 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(2011).

[23] D. Yin, Y. Gu, P. Xue. Speckle-constrained variational methods for image restoration in optical coherence tomography. JOSA A, 30, 878(2013).

[24] X. Ge et al. Deblurring, artifact-free optical coherence tomography with deconvolution-random phase modulation. Opto-Electron. Sci., 3, 230020(2024).

[25] J. M. Schmitt, S. Xiang, K. M. Yung. Speckle in optical coherence tomography. J. Biomed. Opt., 4, 95(1999).

[26] W. Zhao et al. Sparse deconvolution improves the resolution of live-cell super-resolution fluorescence microscopy. Nat. Biotechnol., 40, 606(2022).

[27] A. Krull, T.-O. Buchholz, F. Jug. Noise2void-learning denoising from single noisy images, 2129(2019).

[28] J. Lequyer et al. A fast blind zero-shot denoiser. Nat. Mach. Intell., 4, 953(2022).

[29] H. Zhang et al. Cross-attention learning enables real-time nonuniform rotational distortion correction in oct. Biomed. Opt. Express, 15, 319(2023).

[30] C. Gu et al. Computer-generated holography enables high-uniformity, high-efficiency depth-of-focus extension in endoscopic oct. Opt. Lett., 49, 6896(2024).

[31] Q. Lan et al. OCT as both a shape sensor and a tomographic imager for large-scale freeform robotic scanning. Opt. Lett., 50, 45(2024).

[32] T. Wang et al. Heartbeat OCT: in vivo intravascular megahertz-optical coherence tomography. Biomed Opt Express, 6, 5021(2015).

[33] M. Li et al. OCTA-500: a retinal dataset for optical coherence tomography angiography study. Med. Image Anal., 93, 103092(2024).

[34] J.-L. Starck, E. Pantin, F. Murtagh. Deconvolution in astronomy: a review. Publ. Astron. Soc. Pac., 114, 1051(2002).

[35] O. Ronneberger, P. Fischer, T. Brox. U-net: convolutional networks for biomedical image segmentation, 234(2015).

[36] T. Wang et al. Intravascular optical coherence tomography imaging at 3200 frames per second. Opt. Lett., 38, 1715(2013).

[37] J. Lehtinen et al. Noise2Noise: Learning image restoration without clean data(2018).