Computational optical coherence tomography [Invited]

Ultrasound-induced reorientation for multi-angle optical coherence tomography

Organoid and spheroid technology provide valuable insights into developmental biology and oncology. Optical coherence tomography (OCT) is a label-free technique that has emerged as an excellent tool for monitoring the structure and function of these samples. However, mature organoids are often too opaque for OCT. Access to multi-angle views is highly desirable to overcome this limitation, preferably with non-contact sample handling. To fulfil these requirements, we present an ultrasound-induced reorientation method for multi-angle-OCT, which employs a 3D-printed acoustic trap inserted into an OCT imaging system, to levitate and reorient zebrafish larvae and tumor spheroids in a controlled and reproducible manner. A model-based algorithm was developed for the physically consistent fusion of multi-angle data from a priori unknown angles. We demonstrate enhanced penetration depth in the joint 3D-recovery of reflectivity, attenuation, refractive index, and position registration for zebrafish larvae, creating an enabling tool for future applications in volumetric imaging.

Non-invasive in vivo imaging of human corneal microstructures with optical coherence microscopy

Non-invasive imaging systems with cellular-level resolution offer the opportunity to identify biomarkers of the early stage of corneal diseases, enabling early intervention, monitoring of disease progression, and evaluating treatment efficacy. In this study, a non-contact polarization-dependent optical coherence microscope (POCM) was developed to enable non-invasive in vivo imaging of human corneal microstructures. The system integrated quarter-wave plates into the sample and reference arms of the interferometer to enable deeper penetration of light in tissues as well as mitigate the strong specular reflection from the corneal surface. A common-path approach was adopted to enable control over the polarization in a free space configuration, thus alleviating the need for a broadband polarization-maintained fiber. The POCM achieved volumetric imaging of corneal microstructures, including endothelial cells over a field of view 0.5 × 0.5 mm2 with an almost isotropic resolution of ∼2.2 µm and a volume (500 × 500 × 2048 voxels) rate of 1 Hz. A self-interference approach between the corneal surface and underlying layers was also developed to lessen the corneal curvature and axial motion artifacts, thus enabling high-resolution imaging of microstructures in the anterior cornea, including squamous epithelial cells, wing epithelial cells, basal epithelial cells, sub-basal nerve plexus, and stromal keratocytes.

Correcting spatial-spectral crosstalk and chromatic aberrations in broadband line-scan spectral-domain OCT images

Digital correction of optical aberrations allows for high-resolution imaging across the full depth range in optical coherence tomography (OCT). Many digital aberration correction (DAC) methods have been proposed in the past to evaluate and correct monochromatic error in OCT images. However, other factors that deteriorate the image quality have not been fully investigated. Specifically, in a broadband line-scan spectral-domain OCT system (LS-SD-OCT), photons with different wavelengths scattered from the same transverse location and in the imaged object will be projected onto different spatial coordinates onto the 2D camera sensor, which in this work is defined as spatial-spectral crosstalk. In addition, chromatic aberrations in both axial and lateral directions are not negligible for broad spectral bandwidths. Here we present a novel approach to digital recovery of the spatial resolution in images acquired with a broadband LS-SD-OCT, which addresses these two main factors that limit the effectiveness of DAC for restoring diffraction-limited resolution in LS-SD-OCT images. In the proposed approach, spatial-spectral crosstalk and chromatic aberrations are suppressed by the registration of monochromatic sub-band tomograms that are digitally corrected for aberrations. The new method was validated by imaging a standard resolution target, a microspheres phantom, and different biological tissues. LS-SD-OCT technology combined with the proposed novel image reconstruction method could be a valuable research tool for various biomedical and clinical applications.

Fractal-based aberration-corrected full-field OCT

The Kolmogorov turbulence model has been validated as a quantitative 3D light scattering model of the inhomogeneous refraction index of biological tissue using full-field OCT (FF-OCT). A fractal-based computational compensation approach was proposed for correcting of depth-resolved aberrations with volumetric FF-OCT. First, the power-spectral density spectrum of the index inhomogeneities was measured by radial Fourier transformation of volumetric data. The spectrum's shape indicates the spatial correlation function and can be quantified as the fractal dimension of tissue. The defocusing correction matrix was built by applying fractal-based analysis as an image quality metric. For comparison, tissue-induced in-depth aberration models were built by phase compensation. After digital aberration correction of FF-OCT images, it enables extracting the temporal contrast indicating the sample dynamics in onion in mitosis and ex vivo mouse heart during delayed neuronal death. The proposed fractal-based contrast augmented images show subcellular resolution recording of dynamic scatters of the growing-up onion cell wall and some micro activities. In addition, low-frequency chamber and high-frequency cardiac muscle fibers from ex vivo mouse heart tissue. Therefore, the depth-resolved changes in fractal parameters may be regarded as a quantitative indicator of defocus aberration compensation. Also the enhanced temporal contrast in FF-OCT has the potential to be a label-free, non-invasive, and three-dimensional imaging tool to investigate sub-cellular activities in metabolism studies.

Computational 3D resolution enhancement for optical coherence tomography with a narrowband visible light source

Phase-preserving spectral estimation optical coherence tomography (SE-OCT) enables combining axial resolution improvement with computational depth of field (DOF) extension. We show that the combination of SE-OCT with interferometric synthetic aperture microscopy (ISAM) and computational adaptive optics (CAO) results in high 3D resolution over a large depth range for an OCT system with a narrow bandwidth visible light super-luminescent diode (SLD). SE-OCT results in up to five times axial resolution improvement from 8 µm to 1.5 µm. The combination with ISAM gives a sub-micron lateral resolution over a 400 µm axial range, which is at least 16 times the conventional depth of field. CAO can be successfully applied after SE and ISAM and removes residual aberrations, resulting in high quality images. The results show that phase-preserving SE-OCT is sufficiently accurate for coherent post-processing, enabling the use of cost-effective SLDs in the visible light range for high spatial resolution OCT.

Deep learning-based image enhancement in optical coherence tomography by exploiting interference fringe

Optical coherence tomography (OCT), an interferometric imaging technique, provides non-invasive, high-speed, high-sensitive volumetric biological imaging in vivo. However, systemic features inherent in the basic operating principle of OCT limit its imaging performance such as spatial resolution and signal-to-noise ratio. Here, we propose a deep learning-based OCT image enhancement framework that exploits raw interference fringes to achieve further enhancement from currently obtainable optimized images. The proposed framework for enhancing spatial resolution and reducing speckle noise in OCT images consists of two separate models: an A-scan-based network (NetA) and a B-scan-based network (NetB). NetA utilizes spectrograms obtained via short-time Fourier transform of raw interference fringes to enhance axial resolution of A-scans. NetB was introduced to enhance lateral resolution and reduce speckle noise in B-scan images. The individually trained networks were applied sequentially. We demonstrate the versatility and capability of the proposed framework by visually and quantitatively validating its robust performance. Comparative studies suggest that deep learning utilizing interference fringes can outperform the existing methods. Furthermore, we demonstrate the advantages of the proposed method by comparing our outcomes with multi-B-scan averaged images and contrast-adjusted images. We expect that the proposed framework will be a versatile technology that can improve functionality of OCT.

Evolution of adaptive optics retinal imaging [Invited]

This review describes the progress that has been achieved since adaptive optics (AO) was incorporated into the ophthalmoscope a quarter of a century ago, transforming our ability to image the retina at a cellular spatial scale inside the living eye. The review starts with a comprehensive tabulation of AO papers in the field and then describes the technological advances that have occurred, notably through combining AO with other imaging modalities including confocal, fluorescence, phase contrast, and optical coherence tomography. These advances have made possible many scientific discoveries from the first maps of the topography of the trichromatic cone mosaic to exquisitely sensitive measures of optical and structural changes in photoreceptors in response to light. The future evolution of this technology is poised to offer an increasing array of tools to measure and monitor in vivo retinal structure and function with improved resolution and control.

Tunable image-mapping optical coherence tomography

We present tunable image-mapping optical coherence tomography (TIM-OCT), which can provide optimized imaging performance for a given application by using a programmable phase-only spatial light modulator in a low-coherence full-field spectral-domain interferometer. The resultant system can provide either a high lateral resolution or a high axial resolution in a snapshot without moving parts. Alternatively, the system can achieve a high resolution along all dimensions through a multiple-shot acquisition. We evaluated TIM-OCT in imaging both standard targets and biological samples. Additionally, we demonstrated the integration of TIM-OCT with computational adaptive optics in correcting sample-induced optical aberrations.

Enhanced spectral-domain optical coherence tomography (SD-OCT) using in situ ultrasonic virtual tunable optical waveguides

A conventional optical lens can enhance lateral resolution in optical coherence tomography (OCT) by focusing the input light onto the sample. However, the typical Gaussian beam profile of such a lens will impose a tradeoff between the depth of focus (DOF) and the lateral resolution. The lateral resolution is often compromised to achieve a mm-scale DOF. We have experimentally shown that using a cascade system of an ultrasonic virtual tunable optical waveguide (UVTOW) and a short focal-length lens can provide a large DOF without severely compromising the lateral resolution compared to an external lens with the same effective focal length. In addition, leveraging the reconfigurability of UVTOW, we show that the focal length of the cascade system can be tuned without the need for mechanical translation of the optical lens. We compare the performance of the cascade system with a conventional optical lens to demonstrate enhanced DOF without compromising the lateral resolution as well as reconfigurability of UVTOW for OCT imaging.

Ultra-parallel label-free optophysiology of neural activity

The electrical activity of neurons has a spatiotemporal footprint that spans three orders of magnitude. Traditional electrophysiology lacks the spatial throughput to image the activity of an entire neural network; besides, labeled optical imaging using voltage-sensitive dyes and tracking Ca²⁺ ion dynamics lack the versatility and speed to capture fast-spiking activity, respectively. We present a label-free optical imaging technique to image the changes to the optical path length and the local birefringence caused by neural activity, at 4,000 Hz, across a 200 × 200 μm² region, and with micron-scale spatial resolution and 300-pm displacement sensitivity using Superfast Polarization-sensitive Off-axis Full-field Optical Coherence Microscopy (SPoOF OCM). The undulations in the optical responses from mammalian neuronal activity were matched with field-potential electrophysiology measurements and validated with channel blockers. By directly tracking the widefield neural activity at millisecond timescales and micrometer resolution, SPoOF OCM provides a framework to progress from low-throughput electrophysiology to high-throughput ultra-parallel label-free optophysiology.

Application of Adaptive Optics in Ophthalmology

The eye, the photoreceptive organ used to perceive the external environment, is of great importance to humans. It has been proven that some diseases in humans are accompanied by fundus changes; therefore, the health status of people may be interpreted from retinal images. However, the human eye is not a perfect refractive system for the existence of ocular aberrations. These aberrations not only affect the ability of human visual discrimination and recognition, but restrict the observation of the fine structures of human eye and reduce the possibility of exploring the mechanisms of eye disease. Adaptive optics (AO) is a technique that corrects optical wavefront aberrations. Once integrated into ophthalmoscopes, AO enables retinal imaging at the cellular level. This paper illustrates the principle of AO in correcting wavefront aberrations in human eyes, and then reviews the applications and advances of AO in ophthalmology, including the adaptive optics fundus camera (AO-FC), the adaptive optics scanning laser ophthalmoscope (AO-SLO), the adaptive optics optical coherence tomography (AO-OCT), and their combined multimodal imaging technologies. The future development trend of AO in ophthalmology is also prospected.

Roadmap on digital holography [Invited]

This Roadmap article on digital holography provides an overview of a vast array of research activities in the field of digital holography. The paper consists of a series of 25 sections from the prominent experts in digital holography presenting various aspects of the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications. Each section represents the vision of its author to describe the significant progress, potential impact, important developments, and challenging issues in the field of digital holography.

Ptychographic optical coherence tomography

Ptychography is a robust computational imaging technique that can reconstruct complex light fields beyond conventional hardware limits. However, for many wide-field computational imaging techniques, including ptychography, depth sectioning remains a challenge. Here we demonstrate a high-resolution three-dimensional (3D) computational imaging approach, which combines ptychography with spectral-domain imaging, inspired by optical coherence tomography (OCT). This results in a flexible imaging system with the main advantages of OCT, such as depth-sectioning without sample rotation, decoupling of transverse and axial resolution, and a high axial resolution only determined by the source bandwidth. The interferometric reference needed in OCT is replaced by computational methods, simplifying hardware requirements. As ptychography is capable of deconvolving the illumination contributions in the observed signal, speckle-free images are obtained. We demonstrate the capabilities of ptychographic optical coherence tomography (POCT) by imaging an axially discrete lithographic structure and an axially continuous mouse brain sample.

Modeling, optimization, and validation of an extended-depth-of-field optical coherence tomography probe based on a mirror tunnel

The diagnostic capability of high-resolution optical coherence tomography (OCT) may be enhanced by using extended depth-of-field (EDOF) imaging that retains high transverse resolution over long depths. A recently developed mirror-tunnel optical probe design (single-mode fiber to multimode fiber to lens structure) that generates coaxially focused modes has been previously shown to enable EDOF for endoscopic OCT applications. Here, we present ray-tracing optical modeling of this optical configuration, which has the potential to guide performance improvement through optimization. The Huygens wave propagation of the field was traced through probe components with initial lengths. The irradiance along the x-z plane was analyzed, yielding an average full width at half-maximum (FWHM) of 9 µm over a 640 µm DOF (defined as the axial range over which the beam's transverse FWHM is maintained). A custom merit function was then defined, based on the focal region illumination intensity profile that yielded the maximum possible depth having a constrained FWHM size. An orthogonal gradient descent optimization algorithm was then applied using this merit function, using the multimode fiber, spacer, and lens lengths as variables. Optimization resulted in a modeled mean 6 µm FWHM spot diameter over an EDOF of 1 mm. Following optimization, a probe was fabricated, and was validated using a custom-built near-field scanning pinhole beam profiler. The experimental results (6 µm mean FWHM over 800 µm EDOF) showed reasonable correspondence to the simulated predictions, demonstrating the potential utility of optical modeling and optimization for improving EDOF performance in mirror-tunnel endoscopic OCT probes.

Digital adaptive optics based on digital lateral shearing of the computed pupil field for point scanning retinal swept source OCT

A novel non-iterative digital adaptive optics technique is presented in which the wavefront error is calculated using the phase difference between the pupil field and its digital copies translated by a pixel along the horizontal and vertical direction in the pupil plane. This method provides slope data per pixel, thus can generate > 50k local slope data samples for a circular pupil of diameter 256 pixels with high accuracy and dynamic range. It offers more than 12x faster computational speed in comparison to the sub-aperture based digital adaptive optics method. Furthermore, it is independent of any system parameters, the light distribution in the pupil plane, or the intensity of the image. The technique is useful in applications such as interferometric or digital holography based microscopy, metrology, and as digital wavefront sensor in adaptive optics, where focusing of light in the sample is involved that creates a guide star or where the sample itself exhibits guide star-like structures. This technique is implemented in a point scanning swept-source OCT at 1060 nm, and a large wavefront error with a peak to valley of 20 radians and root mean square error of 0.71 waves is detected and corrected in case of a micro-beads phantom sample. Also, human photoreceptor images are recovered from aberrated retinal OCT volumes acquired at eccentricities of 2 and 2.5 degrees from the fovea in vivo.

Resolution enhancement and realistic speckle recovery with generative adversarial modeling of micro-optical coherence tomography

A resolution enhancement technique for optical coherence tomography (OCT), based on Generative Adversarial Networks (GANs), was developed and investigated. GANs have been previously used for resolution enhancement of photography and optical microscopy images. We have adapted and improved this technique for OCT image generation. Conditional GANs (cGANs) were trained on a novel set of ultrahigh resolution spectral domain OCT volumes, termed micro-OCT, as the high-resolution ground truth (∼1 μm isotropic resolution). The ground truth was paired with a low-resolution image obtained by synthetically degrading resolution 4x in one of (1-D) or both axial and lateral axes (2-D). Cross-sectional image (B-scan) volumes obtained from in vivo imaging of human labial (lip) tissue and mouse skin were used in separate feasibility experiments. Accuracy of resolution enhancement compared to ground truth was quantified with human perceptual accuracy tests performed by an OCT expert. The GAN loss in the optimization objective, noise injection in both the generator and discriminator models, and multi-scale discrimination were found to be important for achieving realistic speckle appearance in the generated OCT images. The utility of high-resolution speckle recovery was illustrated by an example of micro-OCT imaging of blood vessels in lip tissue. Qualitative examples applying the models to image data from outside of the training data distribution, namely human retina and mouse bladder, were also demonstrated, suggesting potential for cross-domain transferability. This preliminary study suggests that deep learning generative models trained on OCT images from high-performance prototype systems may have potential in enhancing lower resolution data from mainstream/commercial systems, thereby bringing cutting-edge technology to the masses at low cost.

Analysis of numerical diffraction calculation methods: from the perspective of phase space optics and the sampling theorem

Diffraction calculations are widely used in applications that require numerical simulation of optical wave propagation. Different numerical diffraction calculation methods have their own transform and sampling properties. In this study, we provide a unified analysis where five popular fast diffraction calculation methods are analyzed from the perspective of phase space optics and the sampling theorem: single fast Fourier transform-based Fresnel transform, Fresnel transfer function approach, Fresnel impulse response approach, angular spectrum method, and Rayleigh-Sommerfeld convolution. The evolutions of an input signal's space-bandwidth product (SBP) during wave propagation are illustrated with the help of a phase space diagram (PSD) and an ABCD matrix. It is demonstrated that all of the above methods cannot make full use of the SBP of the input signal after diffraction; and some transform properties have been ignored. Each method has its own restrictions and applicable range. The reason why different methods have different applicable ranges is explained with physical models. After comprehensively studying and comparing the effect on the SBP and sampling properties of these methods, suggestions are given for choosing the proper method for different applications and overcoming the restrictions of corresponding methods. The PSD and ABCD matrix are used to illustrate the properties of these methods intuitively. Numerical results are presented to verify the analysis, and potential ways to develop new diffraction calculation methods are also discussed.

Micro-optical coherence tomography for high-resolution morphologic imaging of cellular and nerval corneal micro-structures

We demonstrate the highest resolution (1.5×1.5×1 µm) micrometer optical coherence tomography (µOCT) imaging of the morphologic micro-structure of excised swine and non-human primate corneas. Besides epithelial, stromal, and endothelial cell morphology, this report focuses on investigating the most peripheral corneal nerve fibers, the nerve fibers of the subbasal plexus (SBP). Alterations of SBP nerve density and composition are reportedly linked to major neurologic disorders, such as diabetic neuropathy, potentially indicating earliest onsets of denervation. Here, the fine, hyperreflective, epithelial nerve structures located just above Bowman's membrane, are i) visualized using our µOCT prototype, ii) validated by comparison to fluorescence confocal microscopy (including selective immunohistochemical staining), and iii) segmented using state-of-the-art image processing. Here, we also introduce polarization sensitive (PS) µOCT imaging, demonstrating, to the best of our knowledge, the highest resolution corneal PS-OCT scans reported to date.

Three-dimensional imaging with reflection synthetic confocal microscopy

Biomedical imaging lacks label-free microscopy techniques able to reconstruct the contour of biological cells in solution, in 3D and with high resolution, as required for the fast diagnosis of numerous diseases. Inspired by computational optical coherence tomography techniques, we present a tomographic diffractive microscope in reflection geometry used as a synthetic confocal microscope, compatible with this goal and validated with the 3D reconstruction of a human effector T lymphocyte.

Angular compounding for speckle reduction in optical coherence tomography using geometric image registration algorithm and digital focusing

Optical coherence tomography (OCT) suffers from speckle noise due to the high spatial coherence of the utilized light source, leading to significant reductions in image quality and diagnostic capabilities. In the past, angular compounding techniques have been applied to suppress speckle noise. However, existing image registration methods usually guarantee pure angular compounding only within a relatively small field of view in the focal region, but produce spatial averaging in the other regions, resulting in resolution loss and image blur. This work develops an image registration model to correctly localize the real-space location of every pixel in an OCT image, for all depths. The registered images captured at different angles are fused into a speckle-reduced composite image. Digital focusing, based on the convolution of the complex OCT images and the conjugate of the point spread function (PSF), is studied to further enhance lateral resolution and contrast. As demonstrated by experiments, angular compounding with our improved image registration techniques and digital focusing, can effectively suppress speckle noise, enhance resolution and contrast, and reveal fine structures in ex-vivo imaged tissue.

Blur resolved OCT: full-range interferometric synthetic aperture microscopy through dispersion encoding

We present a computational method for full-range interferometric synthetic aperture microscopy (ISAM) under dispersion encoding. With this, one can effectively double the depth range of optical coherence tomography (OCT), whilst dramatically enhancing the spatial resolution away from the focal plane. To this end, we propose a model-based iterative reconstruction (MBIR) method, where ISAM is directly considered in an optimization approach, and we make the discovery that sparsity promoting regularization effectively recovers the full-range signal. Within this work, we adopt an optimal nonuniform discrete fast Fourier transform (NUFFT) implementation of ISAM, which is both fast and numerically stable throughout iterations. We validate our method with several complex samples, scanned with a commercial SD-OCT system with no hardware modification. With this, we both demonstrate full-range ISAM imaging and significantly outperform combinations of existing methods.

Crosstalk-free volumetric in vivo imaging of a human retina with Fourier-domain full-field optical coherence tomography

Fourier-domain full-field optical coherence tomography (FD-FF-OCT) is currently the fastest volumetric imaging technique that is able to generate a single 3-D volume of retina in less than 9 ms, corresponding to a voxel rate of 7.8 GHz. FD-FF-OCT is based on a fast camera, a rapidly tunable laser source, and Fourier-domain signal detection. However, crosstalk appearing due to multiply scattered light corrupts images with the speckle pattern, and therefore, lowers image quality. Here, for the first time, we report on a system that can acquire essentially crosstalk-free volumes of the retina by using a fast deformable membrane. It enables the visualization of choroids and a clear delineation of the retinal layers that is not possible with conventional FD-FF-OCT.

Improve depth of field of optical coherence tomography using finite energy Airy beam

We report a technique to break the depth of field (DOF) limit in optical coherence tomography (OCT) using a finite energy Airy beam. The Airy beam is generated using a phase mask in a Fourier transform schematic and provides the DOF improvement due to its low diffraction. We compare Airy beam OCT with conventional Gaussian beam OCT using lateral resolution and sensitivity. Experimental data from the polystyrene beads in water as well as lemon tissue confirm the extension of DOF up to 10 mm in Airy beam OCT, while the DOF of Gaussian beam OCT is less than 3.0 mm. We also demonstrate that a modified Airy beam can be effectively used in OCT by adjusting the truncating factor of the Airy beam via changing the pattern scale of the phase mask. This result provides a selection method for the use of a finite energy Airy beam in OCT.

Staging mouse preimplantation development in vivo using optical coherence microscopy

In mammals, preimplantation development primarily occurs in the oviduct (or fallopian tube) where fertilized oocytes migrate through, develop and divide as they prepare for implantation in the uterus. Studies of preimplantation development currently rely on ex vivo experiments with the embryos cultured outside of the oviduct, neglecting the native environment for embryonic growth. This prevents the understanding of the natural process of preimplantation development and the roles of the oviduct in early embryonic health. Here, we report an in vivo optical imaging approach enabling high-resolution visualizations of developing embryos in the mouse oviduct. By combining optical coherence microscopy (OCM) and a dorsal imaging window, the subcellular structures and morphologies of unfertilized oocytes, zygotes and preimplantation embryos can be well resolved in vivo, allowing for the staging of development. We present the results together with bright-field microscopy images to show the comparable imaging quality. As the mouse is a well-established model with a variety of genetic engineering strategies available, the in vivo imaging approach opens great opportunities to investigate how the oviduct and early embryos interact to prepare for successful implantation. This knowledge could have beneficial impact on understanding infertility and improving in vitro fertilization. OCM through a dorsal imaging window enables high-resolution imaging and staging of mouse preimplantation embryos in vivo in the oviduct.

Automated sensorless single-shot closed-loop adaptive optics microscopy with feedback from computational adaptive optics

Traditional wavefront-sensor-based adaptive optics (AO) techniques face numerous challenges that cause poor performance in scattering samples. Sensorless closed-loop AO techniques overcome these challenges by optimizing an image metric at different states of a deformable mirror (DM). This requires acquisition of a series of images continuously for optimization - an arduous task in dynamic in vivo samples. We present a technique where the different states of the DM are instead simulated using computational adaptive optics (CAO). The optimal wavefront is estimated by performing CAO on an initial volume to minimize an image metric, and then the pattern is translated to the DM. In this paper, we have demonstrated this technique on a spectral-domain optical coherence microscope for three applications: real-time depth-wise aberration correction, single-shot volumetric aberration correction, and extension of depth-of-focus. Our technique overcomes the disadvantages of sensor-based AO, reduces the number of image acquisitions compared to traditional sensorless AO, and retains the advantages of both computational and hardware-based AO.

Local wavefront mapping in tissue using computational adaptive optics OCT

The identification and correction of wavefront aberrations is often necessary to achieve high-resolution optical images of biological tissues, as imperfections in the optical system and the tissue itself distort the imaging beam. Measuring the localized wavefront aberration provides information on where the beam is distorted and how severely. We have recently developed a method to estimate the single-pass wavefront aberrations from complex optical coherence tomography (OCT) data. Using this method, localized wavefront measurement and correction using computational OCT was performed in ex vivo tissues. The computationally measured wavefront varied throughout the imaged OCT volumes and, therefore, a local wavefront correction outperformed a global wavefront correction. The local wavefront measurement was also used to generate tissue aberration maps. Such aberration maps could potentially be used as a new form of tissue contrast.

Adaptive optics imaging of the human retina

Adaptive Optics (AO) retinal imaging has provided revolutionary tools to scientists and clinicians for studying retinal structure and function in the living eye. From animal models to clinical patients, AO imaging is changing the way scientists are approaching the study of the retina. By providing cellular and subcellular details without the need for histology, it is now possible to perform large scale studies as well as to understand how an individual retina changes over time. Because AO retinal imaging is non-invasive and when performed with near-IR wavelengths both safe and easily tolerated by patients, it holds promise for being incorporated into clinical trials providing cell specific approaches to monitoring diseases and therapeutic interventions. AO is being used to enhance the ability of OCT, fluorescence imaging, and reflectance imaging. By incorporating imaging that is sensitive to differences in the scattering properties of retinal tissue, it is especially sensitive to disease, which can drastically impact retinal tissue properties. This review examines human AO retinal imaging with a concentration on the use of the Adaptive Optics Scanning Laser Ophthalmoscope (AOSLO). It first covers the background and the overall approaches to human AO retinal imaging, and the technology involved, and then concentrates on using AO retinal imaging to study the structure and function of the retina.

Embedded deep learning in ophthalmology: making ophthalmic imaging smarter

Deep learning has recently gained high interest in ophthalmology due to its ability to detect clinically significant features for diagnosis and prognosis. Despite these significant advances, little is known about the ability of various deep learning systems to be embedded within ophthalmic imaging devices, allowing automated image acquisition. In this work, we will review the existing and future directions for 'active acquisition'-embedded deep learning, leading to as high-quality images with little intervention by the human operator. In clinical practice, the improved image quality should translate into more robust deep learning-based clinical diagnostics. Embedded deep learning will be enabled by the constantly improving hardware performance with low cost. We will briefly review possible computation methods in larger clinical systems. Briefly, they can be included in a three-layer framework composed of edge, fog, and cloud layers, the former being performed at a device level. Improved egde-layer performance via 'active acquisition' serves as an automatic data curation operator translating to better quality data in electronic health records, as well as on the cloud layer, for improved deep learning-based clinical data mining.

Optical coherence tomography in Optics Express [Invited]

Optical coherence tomography (OCT) is one of the most successful technologies in the history of biomedical optics. Optics Express played an important role in communicating groundbreaking technological achievements in the field of OCT, and, conversely, OCT papers are among the most frequently cited papers published in Optics Express. On the occasion of the 20th anniversary of the journal, this review analyzes the reasons for the success of OCT papers in Optics Express and discusses possible motivations for researchers to submit some of their best OCT papers to the journal.

Combined hardware and computational optical wavefront correction

In many optical imaging applications, it is necessary to overcome aberrations to obtain high-resolution images. Aberration correction can be performed by either physically modifying the optical wavefront using hardware components, or by modifying the wavefront during image reconstruction using computational imaging. Here we address a longstanding issue in computational imaging: photons that are not collected cannot be corrected. This severely restricts the applications of computational wavefront correction. Additionally, performance limitations of hardware wavefront correction leave many aberrations uncorrected. We combine hardware and computational correction to address the shortcomings of each method. Coherent optical backscattering data is collected using high-speed optical coherence tomography, with aberrations corrected at the time of acquisition using a wavefront sensor and deformable mirror to maximize photon collection. Remaining aberrations are corrected by digitally modifying the coherently-measured wavefront during imaging reconstruction. This strategy obtains high-resolution images with improved signal-to-noise ratio of in vivo human photoreceptor cells with more complete correction of ocular aberrations, and increased flexibility to image at multiple retinal depths, field locations, and time points. While our approach is not restricted to retinal imaging, this application is one of the most challenging for computational imaging due to the large aberrations of the dilated pupil, time-varying aberrations, and unavoidable eye motion. In contrast with previous computational imaging work, we have imaged single photoreceptors and their waveguide modes in fully dilated eyes with a single acquisition. Combined hardware and computational wavefront correction improves the image sharpness of existing adaptive optics systems, and broadens the potential applications of computational imaging methods.

Wavefront measurement using computational adaptive optics

In many optical imaging applications, it is necessary to correct for aberrations to obtain high quality images. Optical coherence tomography (OCT) provides access to the amplitude and phase of the backscattered optical field for three-dimensional (3D) imaging samples. Computational adaptive optics (CAO) modifies the phase of the OCT data in the spatial frequency domain to correct optical aberrations without using a deformable mirror, as is commonly done in hardware-based adaptive optics (AO). This provides improvement of image quality throughout the 3D volume, enabling imaging across greater depth ranges and in highly aberrated samples. However, the CAO aberration correction has a complicated relation to the imaging pupil and is not a direct measurement of the pupil aberrations. Here we present new methods for recovering the wavefront aberrations directly from the OCT data without the use of hardware adaptive optics. This enables both computational measurement and correction of optical aberrations.

Review of optical coherence tomography in oncology

The application of optical coherence tomography (OCT) in the field of oncology has been prospering over the past decade. OCT imaging has been used to image a broad spectrum of malignancies, including those arising in the breast, brain, bladder, the gastrointestinal, respiratory, and reproductive tracts, the skin, and oral cavity, among others. OCT imaging has initially been applied for guiding biopsies, for intraoperatively evaluating tumor margins and lymph nodes, and for the early detection of small lesions that would often not be visible on gross examination, tasks that align well with the clinical emphasis on early detection and intervention. Recently, OCT imaging has been explored for imaging tumor cells and their dynamics, and for the monitoring of tumor responses to treatments. This paper reviews the evolution of OCT technologies for the clinical application of OCT in surgical and noninvasive interventional oncology procedures and concludes with a discussion of the future directions for OCT technologies, with particular emphasis on their applications in oncology.

Clinical translation of handheld optical coherence tomography: practical considerations and recent advancements

Since the inception of optical coherence tomography (OCT), advancements in imaging system design and handheld probes have allowed for numerous advancements in disease diagnostics and characterization of the structural and optical properties of tissue. OCT system developers continue to reduce form factor and cost, while improving imaging performance (speed, resolution, etc.) and flexibility for applicability in a broad range of fields, and nearly every clinical specialty. An extensive array of components to construct customized systems has also become available, with a range of commercial entities that produce high-quality products, from single components to full systems, for clinical and research use. Many advancements in the development of these miniaturized and portable systems can be linked back to a specific challenge in academic research, or a clinical need in medicine or surgery. Handheld OCT systems are discussed and explored for various applications. Handheld systems are discussed in terms of their relative level of portability and form factor, with mention of the supporting technologies and surrounding ecosystem that bolstered their development. Additional insight from our efforts to implement systems in several clinical environments is provided. The trend toward well-designed, efficient, and compact handheld systems paves the way for more widespread adoption of OCT into point-of-care or point-of-procedure applications in both clinical and commercial settings.

Interferometric synthetic aperture microscopy for extended focus optical coherence microscopy

Optical coherence microscopy (OCM) is an interferometric technique providing 3D images of biological samples with micrometric resolution and penetration depth of several hundreds of micrometers. OCM differs from optical coherence tomography (OCT) in that it uses a high numerical aperture (NA) objective to achieve high lateral resolution. However, the high NA also reduces the depth-of-field (DOF), scaling with 1/NA². Interferometric synthetic aperture microscopy (ISAM) is a computed imaging technique providing a solution to this trade-off between resolution and DOF. An alternative hardware method to achieve an extended DOF is to use a non-Gaussian illumination. Extended focus OCM (xfOCM) uses a Bessel beam to obtain a narrow and extended illumination volume. xfOCM detects back-scattered light using a Gaussian mode in order to maintain good sensitivity. However, the Gaussian detection mode limits the DOF. In this work, we present extended ISAM (xISAM), a method combining the benefits of both ISAM and xfOCM. xISAM uses the 3D coherent transfer function (CTF) to generalize the ISAM algorithm to different system configurations. We demonstrate xISAM both on simulated and experimental data, showing that xISAM attains a combination of high transverse resolution and extended DOF which has so far been unobtainable through conventional ISAM or xfOCM individually.

Multiscale sensorless adaptive optics OCT angiography system for in vivo human retinal imaging

We present a multiscale sensorless adaptive optics (SAO) OCT system capable of imaging retinal structure and vasculature with various fields-of-view (FOV) and resolutions. Using a single deformable mirror and exploiting the polarization properties of light, the SAO-OCT-A was implemented in a compact and easy to operate system. With the ability to adjust the beam diameter at the pupil, retinal imaging was demonstrated at two different numerical apertures with the same system. The general morphological structure and retinal vasculature could be observed with a few tens of micrometer-scale lateral resolution with conventional OCT and OCT-A scanning protocols with a 1.7-mm-diameter beam incident at the pupil and a large FOV (15 deg× 15 deg). Changing the system to a higher numerical aperture with a 5.0-mm-diameter beam incident at the pupil and the SAO aberration correction, the FOV was reduced to 3 deg× 3 deg for fine detailed imaging of morphological structure and microvasculature such as the photoreceptor mosaic and capillaries. Multiscale functional SAO-OCT imaging was performed on four healthy subjects, demonstrating its functionality and potential for clinical utility.

Retinal layer segmentation in multiple sclerosis: a systematic review and meta-analysis

BACKGROUND

Structural retinal imaging biomarkers are important for early recognition and monitoring of inflammation and neurodegeneration in multiple sclerosis. With the introduction of spectral domain optical coherence tomography (SD-OCT), supervised automated segmentation of individual retinal layers is possible. We aimed to investigate which retinal layers show atrophy associated with neurodegeneration in multiple sclerosis when measured with SD-OCT.

METHODS

In this systematic review and meta-analysis, we searched for studies in which SD-OCT was used to look at the retina in people with multiple sclerosis with or without optic neuritis in PubMed, Web of Science, and Google Scholar between Nov 22, 1991, and April 19, 2016. Data were taken from cross-sectional cohorts and from one timepoint from longitudinal studies (at least 3 months after onset in studies of optic neuritis). We classified data on eyes into healthy controls, multiple-sclerosis-associated optic neuritis (MSON), and multiple sclerosis without optic neuritis (MSNON). We assessed thickness of the retinal layers and we rated individual layer segmentation performance by random effects meta-analysis for MSON eyes versus control eyes, MSNON eyes versus control eyes, and MSNON eyes versus MSON eyes. We excluded relevant sources of bias by funnel plots.

FINDINGS

Of 25 497 records identified, 110 articles were eligible and 40 reported data (in total 5776 eyes from patients with multiple sclerosis [1667 MSON eyes and 4109 MSNON eyes] and 1697 eyes from healthy controls) that met published OCT quality control criteria and were suitable for meta-analysis. Compared with control eyes, the peripapillary retinal nerve fibre layer (RNFL) showed thinning in MSON eyes (mean difference -20·10 μm, 95% CI -22·76 to -17·44; p<0·0001) and in MSNON eyes (-7·41 μm, -8·98 to -5·83; p<0·0001). The macula showed RNFL thinning of -6·18 μm (-8·07 to -4·28; p<0·0001) in MSON eyes and -2·15 μm (-3·15 to -1·15; p<0·0001) in MSNON eyes compared with control eyes. Atrophy of the macular ganglion cell layer and inner plexiform layer (GCIPL) was -16·42 μm (-19·23 to -13·60; p<0·0001) for MSON eyes and -6·31 μm (-7·75 to -4·87; p<0·0001) for MSNON eyes compared with control eyes. A small degree of inner nuclear layer (INL) thickening occurred in MSON eyes compared with control eyes (0·77 μm, 0·25 to 1·28; p=0·003). We found no statistical difference in the thickness of the combined outer nuclear layer and outer plexiform layer when we compared MSNON or MSON eyes with control eyes, but we found a small degree of thickening of the combined layer when we compared MSON eyes with MSNON eyes (1·21 μm, 0·24 to 2·19; p=0·01).

INTERPRETATION

The largest and most robust differences between the eyes of people with multiple sclerosis and control eyes were found in the peripapillary RNFL and macular GCIPL. Inflammatory disease activity might be captured by the INL. Because of the consistency, robustness, and large effect size, we recommend inclusion of the peripapillary RNFL and macular GCIPL for diagnosis, monitoring, and research.

FUNDING

None.

Introduction to the feature issue on the 25 year anniversary of optical coherence tomography

The guest editors introduce a feature issue commemorating the 25th anniversary of optical coherence tomography.