Multifocal spectral-domain optical coherence tomography based on Bessel beam for extended imaging depth

Yi, Luying; Sun, Liqun; Ding, Wuwen

doi:10.1117/1.jbo.22.10.106016

Cited by 20 publications

(4 citation statements)

References 27 publications

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“…OCT combined with Bessel beams has been shown to enable a large depth range of over 6 mm [ 80 ]. Several OCT modalities utilizing Bessel beams for high-resolution imaging have been reported [ 80 , 81 , 82 , 83 ]. However, there have not been many reports demonstrating their application in ophthalmic imaging.…”

Section: Discussionmentioning

confidence: 99%

Bessel Beams in Ophthalmology: A Review

Suchand Sandeep,

Khairyanto,

Aung

et al. 2023

Micromachines

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The achievable resolution of a conventional imaging system is inevitably limited due to diffraction. Dealing with precise imaging in scattering media, such as in the case of biomedical imaging, is even more difficult owing to the weak signal-to-noise ratios. Recent developments in non-diffractive beams such as Bessel beams, Airy beams, vortex beams, and Mathieu beams have paved the way to tackle some of these challenges. This review specifically focuses on non-diffractive Bessel beams for ophthalmological applications. The theoretical foundation of the non-diffractive Bessel beam is discussed first followed by a review of various ophthalmological applications utilizing Bessel beams. The advantages and disadvantages of these techniques in comparison to those of existing state-of-the-art ophthalmological systems are discussed. The review concludes with an overview of the current developments and the future perspectives of non-diffractive beams in ophthalmology.

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Section: Discussionmentioning

confidence: 99%

Bessel Beams in Ophthalmology: A Review

Suchand Sandeep,

Khairyanto,

Aung

et al. 2023

Micromachines

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“…To extend the depth of focus in OCT imaging, typical hardware approaches, such as binary phase-spatial filters (Kim et al 2017), multi-beam method (Standish et al 2010), and axicons (Yi et al 2017), have been suggested to improve defocus. Compared to hardware-based methods, signal processing methods provide alternative and flexible solutions.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of OCT en face images by unsupervised deep learning

Yuan,

Yang,

Zhao

et al. 2024

Phys. Med. Biol.

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The quality of optical coherence tomography (OCT) en face images is crucial for clinical visualization of early disease. As a three dimensional and coherent imaging, defocus and speckle noise are inevitable, which seriously affect evaluation of microstructure of bio-samples in OCT images. The deep learning has demonstrated great potential in OCT refocusing and denoising, but it is limited by the difficulty of sufficient paired training data. We proposed an unsupervised deep learning-based pipeline to enhance the quality of OCT en face images in this paper. The unregistered defocused conventional OCT images and focused speckle-free OCT images were collected by a home-made speckle modulating OCT system to construct the dataset. The image enhancement model was trained with the cycle training strategy. Finally, the speckle noise and defocus were both effectively improved. The experimental results on complex bio-samples indicated that the proposed method is effective and generalized in enhancing the quality of OCT en face images. The proposed unsupervised deep learning method helps to reduce the complexity of data construction, which is conducive to practical applications in OCT bio-sample imaging.

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“…23 Using the Maxwell equations for the OCT simulations is suitable for modeling complex (profiled) laser beams. [24][25][26][27][28][29] However, it is very time-consuming, even using parallel algorithms, [30][31][32] and requires allocation of massive computer resources that significantly limits the spatial area of interest.…”

Section: Introductionmentioning

confidence: 99%

Imitation of optical coherence tomography images by wave Monte Carlo-based approach implemented with the Leontovich–Fock equation

et al. 2020

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We present a computational modeling approach for imitation of the time-domain optical coherence tomography (OCT) images of biotissues. The developed modeling technique is based on the implementation of the Leontovich-Fock equation into the wave Monte Carlo (MC) method. We discuss the benefits of the developed computational model in comparison to the conventional MC method based on the modeling of OCT images of a nevus. The developed model takes into account diffraction on bulk-absorbing microstructures and allows consideration of the influence of the amplitude-phase profile of the wave beam on the quality of the OCT images. The selection of optical parameters of modeling medium, used for simulation of optical radiation propagation in biotissues, is based on the results obtained experimentally by OCT. The developed computational model can be used for imitation of the light waves propagation both in time-domain and spectral-domain OCT approaches.

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Multifocal spectral-domain optical coherence tomography based on Bessel beam for extended imaging depth

Cited by 20 publications

References 27 publications

Bessel Beams in Ophthalmology: A Review

Bessel Beams in Ophthalmology: A Review

Enhancement of OCT en face images by unsupervised deep learning

Imitation of optical coherence tomography images by wave Monte Carlo-based approach implemented with the Leontovich–Fock equation

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