Computational high-resolution optical imaging of the living human retina

Shemonski, Nathan D.; South, Fredrick A.; Liu, Yuan Zhi; Adie, Steven G.; Carney, P. Scott; Boppart, Stephen A.

doi:10.1038/nphoton.2015.102

Cited by 132 publications

(114 citation statements)

References 23 publications

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“…A complex deconvolution in the form of a frequency domain division is then performed on the whole volumetric image using the PSF obtained from the guide-star. In this deconvolution process, the aberration is cancelled and the optimum resolution can be restored to the image [124]. If the aberrations are spatial variant, multiple guide-stars across the whole field-of-view (2D) or volume (3D) can be picked to correct their local aberrations within each isoplanatic patch.…”

Section: Implementation Of Caomentioning

confidence: 99%

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Computational optical coherence tomography [Invited]

Liu

South

et al. 2017

Biomed. Opt. Express

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Optical coherence tomography (OCT) has become an important imaging modality with numerous biomedical applications. Challenges in high-speed, high-resolution, volumetric OCT imaging include managing dispersion, the trade-off between transverse resolution and depth-of-field, and correcting optical aberrations that are present in both the system and sample. Physics-based computational imaging techniques have proven to provide solutions to these limitations. This review aims to outline these computational imaging techniques within a general mathematical framework, summarize the historical progress, highlight the state-of-the-art achievements, and discuss the present challenges. Swanson, "Optical biopsy and imaging using optical coherence tomography," Nat. Med. 1(9), 970-972 (1995). 3. G. J. Tearney, M. E. Brezinski, B. E. Bouma, S. A. Boppart, C. Pitris, J. F. Southern, and J. G. Fujimoto, "In vivo endoscopic optical biopsy with optical coherence tomography," Science 276(5321), 2037-2039 (1997). 4. S. A. Boppart, B. E. Bouma, C. Pitris, J. F. Southern, M. E. Brezinski, and J. G. Fujimoto, "In vivo cellular optical coherence tomography imaging," Nat. Med. 4(7), 861-865 (1998). Sundaram, P. S. Ray, and S. A. Boppart, "Real-time imaging of the resection bed using a handheld probe to reduce incidence of microscopic positive margins in cancer surgery," Cancer Res. 75(18), 3706-3712 (2015). 9. J. G. Fujimoto and E. A. Swanson, "The development, commercialization, and impact of optical coherence tomography," Invest. Ophthalmol. Vis. Sci. 57(9), OCT1-OCT13 (2016). 10. A. M. Cormack, "Representation of a function by its line integrals, with some radiological applications. II," J.Appl. Phys. 35(10), 2722-2727 (1964). 11. G. N. Hounsfield, "Computerized transverse axial scanning (tomography). 1. Description of system," Br. J.Radiol. 46(552), 1016-1022 (1973). 12. P. C. Lauterbur, "Image formation by induced local interactions: examples employing nuclear magnetic resonance," Nature 242(5394), 190-191 (1973). 13. P. T. Gough and D. W. Hawkins, "Unified framework for modern synthetic aperture imaging algorithms," Int. J.Imaging Syst. Technol. 8(4), 343-358 (1997). shaping for optimal depth-selective focusing in optical coherence tomography," Opt. Express 21(3), 2890-2902 (2013 111-115 (1962). 77. L. Cutrona, E. Leith, C. Palermo, and L. Porcello, "Optical data processing and filtering systems," IRE Trans.Inf. Theory 6(3), 386-400 (1960). 78. L. J. Cutrona, E. N. Leith, L. J. Porcello, and E. W. Vivian, "On the application of coherent optical processing techniques to synthetic-aperture radar," Proc. IEEE 54(8), 1026-1032 (1966). 79. W. Brown and L. Porcello, "An introduction to synthetic-aperture radar," IEEE Spectr. 6(9), 52-62 (1969). 80. M. P. Hayes and P. T. Gough, "Broad-band synthetic aperture sonar," IEEE J. Oceanic Eng. 17(1), 80-94 (1992)

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Section: Implementation Of Caomentioning

confidence: 99%

“…The first published demonstration of CAO in the living human retina was reported by Shemonski et al using an en face OCT imaging system, which operated at a 0.4 MHz pointscanning rate (4 kHz en face line rate) [124]. This high en face frame rate avoided transverse motion of the eye.…”

Section: Applications Of Caomentioning

confidence: 99%

Computational optical coherence tomography [Invited]

Liu

South

et al. 2017

Biomed. Opt. Express

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“…Since defocus is only a special image aberration, higher aberration orders were also corrected, first for scanned [21,22] and later for full-field data [6,7]. Numerical correction of aberrations in full volumes of the human retina was finally demonstrated in vivo by FF-SS-OCT [7].…”

Section: Introductionmentioning

confidence: 99%

“…Contrary to traditional adaptive optics using deformable mirrors and wavefront sensors, correction was performed numerically after the data had been acquired. In addition to previously demonstrated numerical aberration correction on scanned en-face OCT images of the human retina [22], the full-field technique provides entire volumes of living human retina, from which multiple layers with diffraction limited resolution can be extracted.…”

Section: Introductionmentioning

confidence: 99%

Reduction of frame rate in full-field swept-source optical coherence tomography by numerical motion correction [Invited]

Pfäffle

Spahr

Hillmann

et al. 2017

Biomed. Opt. Express

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Full-field swept-source optical coherence tomography (FF-SS-OCT) was recently shown to allow new and exciting applications for imaging the human eye that were previously not possible using current scanning OCT systems. However, especially when using cameras that do not acquire data with hundreds of kHz frame rate, uncorrected phase errors due to axial motion of the eye lead to a drastic loss in image quality of the reconstructed volumes. Here we first give a short overview of recent advances in techniques and applications of parallelized OCT and finally present an iterative and statistical algorithm that estimates and corrects motion-induced phase errors in the FF-SS-OCT data. The presented algorithm is in many aspects adopted from the phase gradient autofocus (PGA) method, which is frequently used in synthetic aperture radar (SAR). Following this approach, the available phase errors can be estimated based on the image information that remains in the data, and no parametrization with few degrees of freedom is required. Consequently, the algorithm is capable of compensating even strong motion artifacts. Efficacy of the algorithm was tested on simulated data with motion containing varying frequency components. We show that even in strongly blurred data, the actual image information remains intact, and the algorithm can identify the phase error and correct it. Furthermore, we use the algorithm to compensate real phase error in FF-SS-OCT imaging of the human retina. Acquisition rates can be reduced by a factor of three (from 60 to 20 kHz frame rate) with an image quality that is even higher compared to uncorrected volumes recorded at the maximum acquisition rate. The presented algorithm for axial motion correction decreases the high requirements on the camera frame rate and thus brings FF-SS-OCT closer to clinical applications.

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“…To ensure high transverse resolution, en face flying spot OCT has been applied for human retinal imaging, which achieves retinal en face images with transverse scanning [13,14]. To be able to realize close to diffraction-limited lateral resolution in OCT retinal imaging, complex hardware adaptive optics (AO) [15][16][17][18][19] or computational AO [20][21][22] would also be needed to correct the aberrations induced by the imperfections of the cornea and lens in the anterior chamber.Full-field OCT (FFOCT) is a kind of time-domain en face parallel OCT that takes images perpendicular to the optical axis without scanning. By using high-NA microscope objectives in a Linnik interferometer, FFOCT is able to achieve standard microscope spatial resolution [23].…”

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confidence: 99%

In vivo high-resolution human retinal imaging with wavefront-correctionless full-field OCT

Xiao¹,

Mazlin²,

Grieve³

et al. 2018

Optica

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As the lateral resolution of full-field optical coherence tomography (FFOCT) with spatially incoherent illumination has been shown to be insensitive to aberrations, we demonstrate high-resolution en face FFOCT retinal imaging without wavefront correction in the human eye in vivo for the first time, to our knowledge. A combination of FFOCT with spectraldomain OCT (SDOCT) is applied for real-time matching of the optical path lengths (OPLs) of FFOCT. Through the realtime cross-sectional SDOCT images, the OPL of the FFOCT reference arm is matched with different retinal layers in the FFOCT sample arm. Thus, diffraction-limited FFOCT images of multiple retinal layers are acquired at both the near periphery and the fovea. The en face FFOCT retinal images reveal information about various structures, such as the nerve fiber orientation, the blood vessel distribution, and the photoreceptor mosaic. During its 25 years of development, optical coherence tomography (OCT) has become a powerful imaging modality in biomedical and clinical studies [1,2]. It has achieved great success in ophthalmology [3], especially in retinal imaging for which it has been entitled the "virtual biopsy" for human retina [4]. Compared with typical retinal imaging modalities like fundus cameras [5] or scanning laser ophthalmoscopy (SLO) [6], in which axial resolution is limited by the finite size of the eye's pupil, OCT offers much higher axial sectioning, as the lateral and axial resolutions are decoupled. The high-resolution cross-sectional depth exploration of the retinal layers offers important information about pathologies for early diagnosis of disease and for tracing disease evolution [7][8][9]. While doctors are capable of interpreting crosssectional OCT slices, there is nevertheless a need for en face views, as shown by the continued use of en face techniques such as fundus cameras or SLO. Thanks to the speed improvement, OCT systems can provide en face retinal images by doing real-time 3Dimaging [10][11][12]. Nevertheless, due to the requirement of large depth of focus, low NA is typically used in traditional OCT, resulting in relatively low spatial resolution compared with high-NA systems. To ensure high transverse resolution, en face flying spot OCT has been applied for human retinal imaging, which achieves retinal en face images with transverse scanning [13,14]. To be able to realize close to diffraction-limited lateral resolution in OCT retinal imaging, complex hardware adaptive optics (AO) [15][16][17][18][19] or computational AO [20][21][22] would also be needed to correct the aberrations induced by the imperfections of the cornea and lens in the anterior chamber.Full-field OCT (FFOCT) is a kind of time-domain en face parallel OCT that takes images perpendicular to the optical axis without scanning. By using high-NA microscope objectives in a Linnik interferometer, FFOCT is able to achieve standard microscope spatial resolution [23]. With spatially incoherent illumination, cross talk is severely inhibited in FFOCT compared with wide-...

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Computational high-resolution optical imaging of the living human retina

Cited by 132 publications

References 23 publications

Computational optical coherence tomography [Invited]

Computational optical coherence tomography [Invited]

Reduction of frame rate in full-field swept-source optical coherence tomography by numerical motion correction [Invited]

In vivo high-resolution human retinal imaging with wavefront-correctionless full-field OCT

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