Speckle-modulating optical coherence tomography in living mice and humans

Unsupervised OCT image despeckling with ground-truth- and repeated-scanning-free features

Optical coherence tomography (OCT) can resolve biological three-dimensional tissue structures, but it is inevitably plagued by speckle noise that degrades image quality and obscures biological structure. Recently unsupervised deep learning methods are becoming more popular in OCT despeckling but they still have to use unpaired noisy-clean images or paired noisy-noisy images. To address the above problem, we propose what we believe to be a novel unsupervised deep learning method for OCT despeckling, termed Double-free Net, which eliminates the need for ground truth data and repeated scanning by sub-sampling noisy images and synthesizing noisier images. In comparison to existing unsupervised methods, Double-free Net obtains superior denoising performance when trained on datasets comprising retinal and human tissue images without clean images. The efficacy of Double-free Net in denoising holds significant promise for diagnostic applications in retinal pathologies and enhances the accuracy of retinal layer segmentation. Results demonstrate that Double-free Net outperforms state-of-the-art methods and exhibits strong convenience and adaptability across different OCT images.

Role of in vivo imaging in Head and Neck cancer management

Intravital microscopy (IVM) and optical coherency tomography (OCT) are powerful optical imaging tools that allow visualization of dynamic biological activities in living subjects with subcellular resolutions. They have been used in preclinical and clinical cancer imaging, providing insights into the complex physiological, cellular, and molecular behaviors of tumors. They have revolutionized cancer diagnosis and therapies, allowing for real-time observation of biologic processes in vivo, including angiogenesis and immune cell interactions. Recent developments in techniques for observing deep tissues of living animals have improved bioluminescent proteins, fluorescent proteins, fluorescent dyes, and detection technologies like two-photon excitation microscopy. These technologies have become indispensable tools in basic sciences, preclinical research, and modern drug development. In Vivo imaging can detect subcellular signaling or metabolic events in living animals, but depth-dependent signal attenuation limits the depth from which significant data can be obtained. Cancer cell motility and invasion are key features of metastatic tumors, but only a small portion of tumor cells are motile and metastasize due to genetic, epigenetic, and microenvironmental heterogeneities.

Self super-resolution of optical coherence tomography images based on deep learning

As a medical imaging modality, many researches have been devoted to improving the resolution of optical coherence tomography (OCT). We developed a deep-learning based OCT self super-resolution (OCT-SSR) pipeline to improve the axial resolution of OCT images based on the high-resolution and low-resolution spectral data collected by the OCT system. In this pipeline, the enhanced super-resolution asymmetric generative adversarial networks were built to improve the network outputs without increasing the complexity. The feasibility and effectiveness of the approach were demonstrated by experimental results on the images of the biological samples collected by the home-made spectral-domain OCT and swept-source OCT systems. More importantly, we found the sidelobes in the original images can be obviously suppressed while improving the resolution based on the OCT-SSR method, which can help to reduce pseudo-signal in OCT imaging when non-Gaussian spectra light source is used. We believe that the OCT-SSR method has broad prospects in breaking the limitation of the source bandwidth on the axial resolution of the OCT system.

SNR-Net OCT: brighten and denoise low-light optical coherence tomography images via deep learning

Low-light optical coherence tomography (OCT) images generated when using low input power, low-quantum-efficiency detection units, low exposure time, or facing high-reflective surfaces, have low bright and signal-to-noise rates (SNR), and restrict OCT technique and clinical applications. While low input power, low quantum efficiency, and low exposure time can help reduce the hardware requirements and accelerate imaging speed; high-reflective surfaces are unavoidable sometimes. Here we propose a deep-learning-based technique to brighten and denoise low-light OCT images, termed SNR-Net OCT. The proposed SNR-Net OCT deeply integrated a conventional OCT setup and a residual-dense-block U-Net generative adversarial network with channel-wise attention connections trained using a customized large speckle-free SNR-enhanced brighter OCT dataset. Results demonstrated that the proposed SNR-Net OCT can brighten low-light OCT images and remove the speckle noise effectively, with enhancing SNR and maintaining the tissue microstructures well. Moreover, compared to the hardware-based techniques, the proposed SNR-Net OCT can be of lower cost and better performance.

Visible-Light Optical Coherence Tomography Fibergraphy of the Tree Shrew Retinal Ganglion Cell Axon Bundles

We seek to develop techniques for high-resolution imaging of the tree shrew retina for visualizing and parameterizing retinal ganglion cell (RGC) axon bundles in vivo. We applied visible-light optical coherence tomography fibergraphy (vis-OCTF) and temporal speckle averaging (TSA) to visualize individual RGC axon bundles in the tree shrew retina. For the first time, we quantified individual RGC bundle width, height, and cross-sectional area and applied vis-OCT angiography (vis-OCTA) to visualize the retinal microvasculature in tree shrews. Throughout the retina, as the distance from the optic nerve head (ONH) increased from 0.5 mm to 2.5 mm, bundle width increased by 30%, height decreased by 67%, and cross-sectional area decreased by 36%. We also showed that axon bundles become vertically elongated as they converge toward the ONH. Ex vivo confocal microscopy of retinal flat-mounts immunostained with Tuj1 confirmed our in vivo vis-OCTF findings.

Fluorescence enhancement of organic dyes by femtosecond laser-induced cavitation bubbles for crystal imaging

Fluorescence from organic dyes can be applied in many research fields such as imaging, bio-sensing and diagnosis. One shortcoming of fluorescence imaging is the limitation in emission intensity. Amplification of fluorescence signals can be achieved by the enhancement of localized electromagnetic fields. Metallic nanoparticles are widely applied to produce plasmon resonance, but they cause thermal damage to fragile bio-materials. In this study, we propose a method for nanoparticle-free fluorescence enhancement by ultrafast laser-induced cavitation bubbles in organic dye solutions. Fluorescence enhancement without the use of nanoparticles prevents potential hazards including thermal effects and biotoxicity. In order to achieve fluorescence enhancement in neat dye solution, cavitation bubbles were induced by focusing an 800 nm ultrafast laser beam. Another 400 nm laser beam was used to pump the gain medium. Fluorescence enhancement was observed in various dye solutions. The intensity and spectra of the fluorescence emission can be controlled by changing the power and focus of the excitation laser. According to time-resolved microscopy and simulation results, the cavity formed by the laser-induced bubbles results in the enhancement of the localized electromagnetic field and induces the amplification of the fluorescence signal. The bubble-enhanced fluorescence emission was used for imaging of protein crystals without causing thermal damage to the samples. This study provides an effective method for bio-compatible fluorescence enhancement and has application prospects in fields such as bio-imaging.

Revealing the Meissner Corpuscles in Human Glabrous Skin Using In Vivo Non-Invasive Imaging Techniques

The presence of mechanoreceptors in glabrous skin allows humans to discriminate textures by touch. The amount and distribution of these receptors defines our tactile sensitivity and can be affected by diseases such as diabetes, HIV-related pathologies, and hereditary neuropathies. The quantification of mechanoreceptors as clinical markers by biopsy is an invasive method of diagnosis. We report the localization and quantification of Meissner corpuscles in glabrous skin using in vivo, non-invasive optical microscopy techniques. Our approach is supported by the discovery of epidermal protrusions which are co-localized with Meissner corpuscles. Index fingers, small fingers, and tenar palm regions of ten participants were imaged by optical coherence tomography (OCT) and laser scan microscopy (LSM) to determine the thickness of the stratum corneum and epidermis and to count the Meissner corpuscles. We discovered that regions containing Meissner corpuscles could be easily identified by LSM with an enhanced optical reflectance above the corpuscles, caused by a protrusion of the strongly reflecting epidermis into the stratum corneum with its weak reflectance. We suggest that this local morphology above Meissner corpuscles has a function in tactile perception.

Live 4D-OCT denoising with self-supervised deep learning

By providing three-dimensional visualization of tissues and instruments at high resolution, live volumetric optical coherence tomography (4D-OCT) has the potential to revolutionize ophthalmic surgery. However, the necessary imaging speed is accompanied by increased noise levels. A high data rate and the requirement for minimal latency impose major limitations for real-time noise reduction. In this work, we propose a low complexity neural network for denoising, directly incorporated into the image reconstruction pipeline of a microscope-integrated 4D-OCT prototype with an A-scan rate of 1.2 MHz. For this purpose, we trained a blind-spot network on unpaired OCT images using a self-supervised learning approach. With an optimized U-Net, only a few milliseconds of additional latency were introduced. Simultaneously, these architectural adaptations improved the numerical denoising performance compared to the basic setup, outperforming non-local filtering algorithms. Layers and edges of anatomical structures in B-scans were better preserved than with Gaussian filtering despite comparable processing time. By comparing scenes with and without denoising employed, we show that neural networks can be used to improve visual appearance of volumetric renderings in real time. Enhancing the rendering quality is an important step for the clinical acceptance and translation of 4D-OCT as an intra-surgical guidance tool.

Role of basal sweating in maintaining skin hydration in the finger: A long-standing paradox in dry skin resolved

A long-standing paradox in dermatology is why skin dehydration in the fingers can be triggered by repeated water exposure despite the action of water to hydrate skin tissue. Potential clues might be provided by identifying a mechanism through which water is held in the skin of the fingers. We speculated that this mechanism would be impaired after repeated water exposure. Here, we investigated whether there might be glabrous skin-specific water-holding machinery and whether this machinery might be impaired in dry skin/hand eczema. We examined this by using an impression-mould technique, allowing for an accurate quantification of sweat gland/duct activity and optical coherence tomography. Unlike in hairy skin, sweat pores were rarely detected at the folds of the finger at baseline. Surprisingly, after water exposure, sweat pores at the folds opened and those at the ridges closed in healthy controls (HCs). Sweating in the dermal folds of the hands correlated with skin hydration, and decreased in dry skin/hand eczema, suggesting that its impairment may be one of the causes of dry skin. After repeated water exposure, basal sweating response at the folds was exhausted in patients with dry skin/hand eczema as well as HCs. This exhaustion was rescued by exposing individuals to high humidity. Basal sweating defects would be a target for dry skin/hand eczema. Maintaining basal sweating responses in the finger is the best preventive measures in achieving prevention of dry skin/hand eczema.

Computational 3D microscopy with optical coherence refraction tomography

Optical coherence tomography (OCT) has seen widespread success as an in vivo clinical diagnostic 3D imaging modality, impacting areas including ophthalmology, cardiology, and gastroenterology. Despite its many advantages, such as high sensitivity, speed, and depth penetration, OCT suffers from several shortcomings that ultimately limit its utility as a 3D microscopy tool, such as its pervasive coherent speckle noise and poor lateral resolution required to maintain millimeter-scale imaging depths. Here, we present 3D optical coherence refraction tomography (OCRT), a computational extension of OCT which synthesizes an incoherent contrast mechanism by combining multiple OCT volumes, acquired across two rotation axes, to form a resolution-enhanced, speckle-reduced, refraction-corrected 3D reconstruction. Our label-free computational 3D microscope features a novel optical design incorporating a parabolic mirror to enable the capture of 5D plenoptic datasets, consisting of millimetric 3D fields of view over up to ±75° without moving the sample. We demonstrate that 3D OCRT reveals 3D features unobserved by conventional OCT in fruit fly, zebrafish, and mouse samples.

Hybrid-structure network and network comparative study for deep-learning-based speckle-modulating optical coherence tomography

Optical coherence tomography (OCT), a promising noninvasive bioimaging technique, can resolve sample three-dimensional microstructures. However, speckle noise imposes obvious limitations on OCT resolving capabilities. Here we proposed a deep-learning-based speckle-modulating OCT based on a hybrid-structure network, residual-dense-block U-Net generative adversarial network (RDBU-Net GAN), and further conducted a comprehensively comparative study to explore multi-type deep-learning architectures' abilities to extract speckle pattern characteristics and remove speckle, and resolve microstructures. This is the first time that network comparative study has been performed on a customized dataset containing mass more-general speckle patterns obtained from a custom-built speckle-modulating OCT, but not on retinal OCT datasets with limited speckle patterns. Results demonstrated that the proposed RDBU-Net GAN has a more excellent ability to extract speckle pattern characteristics and remove speckle, and resolve microstructures. This work will be useful for future studies on OCT speckle removing and deep-learning-based speckle-modulating OCT.

Local Burr distribution estimator for speckle statistics

Speckle statistics in ultrasound and optical coherence tomography have been studied using various distributions, including the Rayleigh, the K, and the more recently proposed Burr distribution. In this paper, we expand on the utility of the Burr distribution by first validating its theoretical framework with numerical simulations and then introducing a new local estimator to characterize sample tissues of liver, brain, and skin using optical coherence tomography. The spatially local estimates of the Burr distribution's power-law or exponent parameter enable a new type of parametric image. The simulation and experimental results confirm the potential for various applications of the Burr distribution in both basic science and clinical realms.

In vivo Imaging of Retina and Choroid in Guinea Pigs

Purpose: To evaluate the feasibility of in-vivo imaging of the retina and choroid using spectral domain optical coherence tomography (OCT) in guinea pigs. Methods: The study included 19 pigmented guinea pigs (age: 3-4 weeks) which underwent sonographic axial length measurements and OCT imaging. At study end, the animals were sacrificed and histomorphometric examinations of the retina and choroid were performed. We assessed the reproducibility of the OCT measurements and compared in-vivo measurements to histomorphometric data. Results: The mean thickness of the retina and choroid near the optic nerve head was 175.6 ± 25.8 and 63.4 ± 16.5 μm, respectively, and mean Bruch's membrane opening (BMO) diameter was 831 ± 121 μm. The intra-observer comparison of measurements of retinal thickness (intraclass correlation coefficient (ICC) = 0.92, 95% CI: 0.86-0.96; P < 0.001), choroidal thickness (ICC = 0.92, 95% CI: 0.86-0.96; P < 0.001), and BMO diameter (ICC = 0.92, 95% CI: 0.86-0.96; P < 0.001) showed a high correlation. A high agreement was present also for the inter-observer reproducibility of the measurements of retinal thickness (Pearson correlation coefficient (R) = 0.98; P < 0.001), choroidal thickness (R = 0.96; P < 0.001), and BMO diameter (R = 0.98; P < 0.001). The Bland-Altman plots showed that 2.6% (1/38), 5.3% (2/38), and 7.9% (3/38) of the measurement points of retinal thickness, choroidal thickness and BMO diameter, respectively, were located outside of the 95% limits of agreement. The OCT-based thickness measurements of retina and choroid were significantly higher than those measured by histomorphometry (both P-values <0.01). Conclusion: OCT-based in-vivo morphometric imaging of the retina and choroid in guinea pigs is feasible with an acceptable intra-observer repeatability and inter-observer reproducibility.

Analysis of Parainflammation in Chronic Glaucoma Using Vitreous-OCT Imaging

Glaucoma causes blindness due to the progressive death of retinal ganglion cells. The immune response chronically and subclinically mediates a homeostatic role. In current clinical practice, it is impossible to analyse neuroinflammation non-invasively. However, analysis of vitreous images using optical coherence tomography detects the immune response as hyperreflective opacities. This study monitors vitreous parainflammation in two animal models of glaucoma, comparing both healthy controls and sexes over six months. Computational analysis characterizes in vivo the hyperreflective opacities, identified histologically as hyalocyte-like Iba-1+ (microglial marker) cells. Glaucomatous eyes showed greater intensity and number of vitreous opacities as well as dynamic fluctuations in the percentage of activated cells (50–250 microns²) vs. non-activated cells (10–50 microns²), isolated cells (10 microns²) and complexes (>250 microns²). Smaller opacities (isolated cells) showed the highest mean intensity (intracellular machinery), were the most rounded at earlier stages (recruitment) and showed the greatest change in orientation (motility). Study of vitreous parainflammation could be a biomarker of glaucoma onset and progression.

Ultra-widefield photoacoustic microscopy with a dual-channel slider-crank laser-scanning apparatus for in vivo biomedical study

Photoacoustic microscopy (PAM) is an important imaging tool that can noninvasively visualize the anatomical structure of living animals. However, the limited scanning area restricts traditional PAM systems for scanning a large animal. Here, we firstly report a dual-channel PAM system based on a custom-made slider-crank scanner. This novel scanner allows us to stably capture an ultra-widefield scanning area of 24 mm at a high B-scan speed of 32 Hz while maintaining a high signal-to-noise ratio. Our system's spatial resolution is measured at ∼3.4 μm and ∼37 μm for lateral and axial resolution, respectively. Without any contrast agent, a dragonfly wing, a nude mouse ear, an entire rat ear, and a portion of mouse sagittal are successfully imaged. Furthermore, for hemodynamic monitoring, the mimicking circulating tumor cells using magnetic contrast agent is rapidly captured in vitro. The experimental results demonstrated that our device is a promising tool for biological applications.

Sm-Net OCT: a deep-learning-based speckle-modulating optical coherence tomography

Speckle imposes obvious limitations on resolving capabilities of optical coherence tomography (OCT), while speckle-modulating OCT can efficiently reduce speckle arbitrarily. However, speckle-modulating OCT seriously reduces the imaging sensitivity and temporal resolution of the OCT system when reducing speckle. Here, we proposed a deep-learning-based speckle-modulating OCT, termed Sm-Net OCT, by deeply integrating conventional OCT setup and generative adversarial network trained with a customized large speckle-modulating OCT dataset containing massive speckle patterns. The customized large speckle-modulating OCT dataset was obtained from the aforementioned conventional OCT setup rebuilt into a speckle-modulating OCT and performed imaging using different scanning parameters. Experimental results demonstrated that the proposed Sm-Net OCT can effectively obtain high-quality OCT images without the electronic noise and speckle, and conquer the limitations of reducing the imaging sensitivity and temporal resolution which conventional speckle-modulating OCT has. The proposed Sm-Net OCT can significantly improve the adaptability and practicality capabilities of OCT imaging, and expand its application fields.

Modeling of Retinal Optical Coherence Tomography Based on Stochastic Differential Equations: Application to Denoising

In this paper a statistical modeling, based on stochastic differential equations (SDEs), is proposed for retinal Optical Coherence Tomography (OCT) images. In this method, pixel intensities of image are considered as discrete realizations of a Levy stable process. This process has independent increments and can be expressed as response of SDE to a white symmetric alpha stable (s [Formula: see text]) noise. Based on this assumption, applying appropriate differential operator makes intensities statistically independent. Mentioned white stable noise can be regenerated by applying fractional Laplacian operator to image intensities. In this way, we modeled OCT images as s [Formula: see text] distribution. We applied fractional Laplacian operator to image and fitted s [Formula: see text] to its histogram. Statistical tests were used to evaluate goodness of fit of stable distribution and its heavy tailed and stability characteristics. We used modeled s [Formula: see text] distribution as prior information in maximum a posteriori (MAP) estimator in order to reduce the speckle noise of OCT images. Such a statistically independent prior distribution simplified denoising optimization problem to a regularization algorithm with an adjustable shrinkage operator for each image. Alternating Direction Method of Multipliers (ADMM) algorithm was utilized to solve the denoising problem. We presented visual and quantitative evaluation results of the performance of this modeling and denoising methods for normal and abnormal images. Applying parameters of model in classification task as well as indicating effect of denoising in layer segmentation improvement illustrates that the proposed method describes OCT data more accurately than other models that do not remove statistical dependencies between pixel intensities.

Speckle statistics of biological tissues in optical coherence tomography

The speckle statistics of optical coherence tomography images of biological tissue have been studied using several historical probability density functions. Here, we propose a new theoretical framework based on power-law functions, where we hypothesize that an underlying power-law distribution governs scattering from tissues. Thus, multi-scale scattering sites including the fractal branching vasculature will contribute to power-law probability distributions of speckle statistics. Specifically, these are the Burr type XII distribution for speckle amplitude, the Lomax distribution for intensity, and the generalized logistic distribution for log amplitude. Experimentally, these three distributions are fitted to histogram data from nine optical coherence tomography scans of various samples and biological tissues, in vivo and ex vivo. The distributions are also compared with classical models such as the Rayleigh, K, and gamma distributions. The results indicate that across OCT datasets of various tissue types, the proposed power-law distributions are more appropriate models yielding novel parameters for characterizing the physics of scattering from biological tissue. Thus, the overall framework brings to the field new biomarkers from OCT measures of speckle in tissues, grounded in basic biophysics and with wide applications to diagnostic imaging in clinical use.

Fast OCT image enhancement method based on the sigmoid-energy conservation equation

Optical coherence tomography (OCT) is an important medical diagnosis technology, but OCT images are inevitably interfered by speckle noise and other factors, which greatly reduce the quality of the OCT image. In order to improve the quality of the OCT image quickly, a fast OCT image enhancement method is proposed based on the fusion equation. The proposed method consists of three parts: edge detection, noise suppression, and image fusion. In this paper, the improved wave algorithm is used to detect the image edge and its fine features, and the averaging uncorrelated images method is used to suppress speckle noise and improve image contrast. In order to sharpen image edges while suppressing the speckle noise, a sigmoid-energy conservation equation (SE equation) is designed to fuse the edge detection image and the noise suppression image. The proposed method was tested on two publicly available datasets. Results show that the proposed method can effectively improve image contrast and sharpen image edges while suppressing the speckle noise. Compared with other state-of-the-art methods, the proposed method has better image enhancement effect and speed. Under the same or better enhancement effect, the processing speed of the proposed method is 2 ∼ 34 times faster than other methods.

Monitoring New Long-Lasting Intravitreal Formulation for Glaucoma with Vitreous Images Using Optical Coherence Tomography

Intravitreal injection is the gold standard therapeutic option for posterior segment pathologies, and long-lasting release is necessary to avoid reinjections. There is no effective intravitreal treatment for glaucoma or other optic neuropathies in daily practice, nor is there a non-invasive method to monitor drug levels in the vitreous. Here we show that a glaucoma treatment combining a hypotensive and neuroprotective intravitreal formulation (IF) of brimonidine–Laponite (BRI/LAP) can be monitored non-invasively using vitreoretinal interface imaging captured with optical coherence tomography (OCT) over 24 weeks of follow-up. Qualitative and quantitative characterisation was achieved by analysing the changes in vitreous (VIT) signal intensity, expressed as a ratio of retinal pigment epithelium (RPE) intensity. Vitreous hyperreflective aggregates mixed in the vitreous and tended to settle on the retinal surface. Relative intensity and aggregate size progressively decreased over 24 weeks in treated rat eyes as the BRI/LAP IF degraded. VIT/RPE relative intensity and total aggregate area correlated with brimonidine levels measured in the eye. The OCT-derived VIT/RPE relative intensity may be a useful and objective marker for non-invasive monitoring of BRI/LAP IF.

Weakly Supervised Deep Learning-Based Optical Coherence Tomography Angiography

Optical coherence tomography angiography (OCTA) is a promising imaging modality for microvasculature studies. Deep learning networks have been widely applied in the field of OCTA reconstruction, benefiting from its powerful mapping capability among images. However, these existing deep learning-based methods depend on high-quality labels, which are hard to acquire considering imaging hardware limitations and practical data acquisition conditions. In this article, we proposed an unprecedented weakly supervised deep learning-based pipeline for OCTA reconstruction task, in the absence of high-quality training labels. The proposed pipeline was investigated on an in vivo animal dataset and a human eye dataset by a cross-validation strategy. Compared with supervised learning approaches, the proposed approach demonstrated similar or even better performance in the OCTA reconstruction task. These investigations indicate that the proposed weakly supervised learning strategy is well capable of performing OCTA reconstruction, and has a certain potential towards clinical applications.

Scattering-Based Light-Sheet Microscopy for Rapid Cellular Imaging of Fresh Tissue

BACKGROUND AND OBJECTIVES

Light-sheet microscopy (LSM) is a novel imaging technology that has been used for imaging fluorescence contrast in basic life science research. In this paper, we have developed a scattering-based LSM (sLSM) for rapidly imaging the cellular morphology of fresh tissues without any exogenous fluorescent dyes.

STUDY DESIGN/MATERIALS AND METHODS

In the sLSM device, a thin light sheet with the central wavelength of 834 nm was incident on the tissue obliquely, 45° relative to the tissue surface. The detection optics was configured to map the light sheet-illuminated area onto a two-dimensional imaging sensor. The illumination numerical aperture (NA) was set as 0.0625, and the detection NA 0.3.

RESULTS

The sLSM device achieved a light sheet thickness of less than 6.7 µm over 284 µm along the illumination optical axis. The detection optics of the sLSM device had a resolution of 1.8 µm. The sLSM images of the swine kidney ex vivo visualized tubules with similar sizes and shapes to those observed in histopathologic images. The swine duodenum sLSM images revealed cell nuclei and villi architecture in superficial lesions and glands in deeper regions.

CONCLUSIONS

The preliminary results suggest that sLSM may have the potential for rapidly examining the freshly-excised tissue ex vivo or intact tissue in vivo at microscopic resolution. Further optimization and performance evaluation of the sLSM technology will be needed in the future. Lasers Surg. Med. © 2020 Wiley Periodicals LLC.

Dynamic contrast in scanning microscopic OCT

While optical coherence tomography (OCT) provides a resolution down to 1 µm, it has difficulties in visualizing cellular structures due to a lack of scattering contrast. By evaluating signal fluctuations, a significant contrast enhancement was demonstrated using time-domain full-field OCT (FF-OCT), which makes cellular and subcellular structures visible. The putative cause of the dynamic OCT signal is the site-dependent active motion of cellular structures in a sub-micrometer range, which provides histology-like contrast. Here we demonstrate dynamic contrast with a scanning frequency-domain OCT (FD-OCT), which we believe has crucial advantages. Given the inherent sectional imaging geometry, scanning FD-OCT provides depth-resolved images across tissue layers, a perspective known from histopathology, much faster and more efficiently than FF-OCT. Both shorter acquisition times and tomographic depth-sectioning reduce the sensitivity of dynamic contrast for bulk tissue motion artifacts and simplify their correction in post-processing. Dynamic contrast makes microscopic FD-OCT a promising tool for the histological analysis of unstained tissues.

Development of a 3-D Physical Dynamics Monitoring System Using OCM with DVC for Quantification of Sprouting Endothelial Cells Interacting with a Collagen Matrix

The extracellular matrix (ECM) plays a key role during cell migration, proliferation, and differentiation by providing adhesion sites and serving as a physical scaffold. Elucidating the interaction between the cell and ECM can reveal the underlying mechanisms of cellular behavior that are currently unclear. Analysis of the deformation of the ECM due to cell-matrix interactions requires microscopic, three-dimensional (3-D) imaging methods, such as confocal microscopy and second-harmonic generation microscopy, which are currently limited by phototoxicity and bleaching as a result of the point-scanning approach. In this study, we suggest the use of optical coherence microscopy (OCM) as a live-cell, volumetric, fast imaging tool for analyzing the deformation of fibrous ECM. We optimized such OCM parameters as the sampling rate to obtain images of the best quality that meet the requirements for robust digital volume correlation (DVC) analysis. Visualization and analysis of the mechanical interaction between collagen ECM and human umbilical vein endothelial cells (HUVECs) show that cellular adhesion during protrusion can be analyzed and quantified. The advantages of OCM, such as fine isotropic spatial resolution, fast time resolution, and low phototoxicity, make it the ideal optic tool for 3-D traction force microscopy.

Optical coherence tomography image denoising using a generative adversarial network with speckle modulation

Optical coherence tomography (OCT) is widely used for biomedical imaging and clinical diagnosis. However, speckle noise is a key factor affecting OCT image quality. Here, we developed a custom generative adversarial network (GAN) to denoise OCT images. A speckle-modulating OCT (SM-OCT) was built to generate low speckle images to be used as the ground truth. In total, 210 000 SM-OCT images were used for training and validating the neural network model, which we call SM-GAN. The performance of the SM-GAN method was further demonstrated using online benchmark retinal images, 3D OCT images acquired from human fingers and OCT videos of a beating fruit fly heart. The denoise performance of the SM-GAN model was compared to traditional OCT denoising methods and other state-of-the-art deep learning based denoise networks. We conclude that the SM-GAN model presented here can effectively reduce speckle noise in OCT images and videos while maintaining spatial and temporal resolutions.

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.

Speckle reducing OCT using optical chopper

Optical coherence tomography (OCT) has been an important and powerful tool for biological research and clinical applications. However, speckle noise significantly degrades the image quality of OCT and has a negative impact on the clinical diagnosis accuracy. In this paper, we propose a novel speckle noise suppression technique which changes the spatial distribution of sample beam using a special optical chopper. Then a series of OCT images with uncorrelated speckle patterns could be captured and compounded to improve the image quality without degradation of resolution. Typical signal-to-noise ratio improvement of ∼6.4 dB is experimentally achieved in tissue phantom imaging with average number n = 100. Furthermore, compared with conventional OCT, the proposed technique is demonstrated to view finer and clearer biological structures in human skin in vivo, such as sweat glands and blood vessels. The advantages of low cost, simple structure and compact integration will benefit the future design of handheld or endoscopic probe for biomedical imaging in research and clinical applications.

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.

Speckle reduction in visible-light optical coherence tomography using scan modulation

We present a technique to reduce speckle in visible-light optical coherence tomography (vis-OCT) that preserves fine structural details and is robust against sample motion. Specifically, we locally modulate B-scans orthogonally to their axis of acquisition. Such modulation enables acquisition of uncorrelated speckle patterns from similar anatomical locations, which can be averaged to reduce speckle. To verify the effectiveness of speckle reduction, we performed in-vivo retinal imaging using modulated raster and circular scans in both mice and humans. We compared speckle-reduced vis-OCT images with the images acquired with unmodulated B-scans from the same anatomical locations. We compared contrast-to-noise ratio (CNR) and equivalent number of looks (ENL) to quantify the image quality enhancement. Speckle-reduced images showed up to a 2.35-dB improvement in CNR and up to a 3.1-fold improvement in ENL with more discernable anatomical features using eight modulated A-line averages at a 25-kHz A-line rate.

Phase-sensitive interferometry of decorrelated speckle patterns

Phase-sensitive coherent imaging exploits changes in the phases of backscattered light to observe tiny alterations of scattering structures or variations of the refractive index. But moving scatterers or a fluctuating refractive index decorrelate the phases and speckle patterns in the images. It is generally believed that once the speckle pattern has changed, the phases are scrambled and any meaningful phase difference to the original pattern is removed. As a consequence, diffusion and tissue motion that cannot be resolved, prevent phase-sensitive imaging of biological specimens. Here, we show that a phase comparison between decorrelated speckle patterns is still possible by utilizing a series of images acquired during decorrelation. The resulting evaluation scheme is mathematically equivalent to methods for astronomic imaging through the turbulent sky by speckle interferometry. We thus adopt the idea of speckle interferometry to phase-sensitive imaging in biological tissues and demonstrate its efficacy for simulated data and imaging of photoreceptor activity with phase-sensitive optical coherence tomography. We believe the described methods can be applied to many imaging modalities that use phase values for interferometry.

Spatiotemporal Tracking of Brain-Tumor-Associated Myeloid Cells in Vivo through Optical Coherence Tomography with Plasmonic Labeling and Speckle Modulation

By their nature, tumors pose a set of profound challenges to the immune system with respect to cellular recognition and response coordination. Recent research indicates that leukocyte subpopulations, especially tumor-associated macrophages (TAMs), can exert substantial influence on the efficacy of various cancer immunotherapy treatment strategies. To better study and understand the roles of TAMs in determining immunotherapeutic outcomes, significant technical challenges associated with dynamically monitoring single cells of interest in relevant live animal models of solid tumors must be overcome. However, imaging techniques with the requisite combination of spatiotemporal resolution, cell-specific contrast, and sufficient signal-to-noise at increasing depths in tissue are exceedingly limited. Here we describe a method to enable high-resolution, wide-field, longitudinal imaging of TAMs based on speckle-modulating optical coherence tomography (SM-OCT) and spectral scattering from an optimized contrast agent. The approach's improvements to OCT detection sensitivity and noise reduction enabled high-resolution OCT-based observation of individual cells of a specific host lineage in live animals. We found that large gold nanorods (LGNRs) that exhibit a narrow-band, enhanced scattering cross-section can selectively label TAMs and activate microglia in an in vivo orthotopic murine model of glioblastoma multiforme. We demonstrated near real-time tracking of the migration of cells within these myeloid subpopulations. The intrinsic spatiotemporal resolution, imaging depth, and contrast sensitivity reported herein may facilitate detailed studies of the fundamental behaviors of TAMs and other leukocytes at the single-cell level in vivo, including intratumoral distribution heterogeneity and roles in modulating cancer proliferation.

Speckle modulation enables high-resolution wide-field human brain tumor margin detection and in vivo murine neuroimaging

Current in vivo neuroimaging techniques provide limited field of view or spatial resolution and often require exogenous contrast. These limitations prohibit detailed structural imaging across wide fields of view and hinder intraoperative tumor margin detection. Here we present a novel neuroimaging technique, speckle-modulating optical coherence tomography (SM-OCT), which allows us to image the brains of live mice and ex vivo human samples with unprecedented resolution and wide field of view using only endogenous contrast. The increased visibility provided by speckle elimination reveals white matter fascicles and cortical layer architecture in brains of live mice. To our knowledge, the data reported herein represents the highest resolution imaging of murine white matter structure achieved in vivo across a wide field of view of several millimeters. When applied to an orthotopic murine glioblastoma xenograft model, SM-OCT readily identifies brain tumor margins with resolution of approximately 10 μm. SM-OCT of ex vivo human temporal lobe tissue reveals fine structures including cortical layers and myelinated axons. Finally, when applied to an ex vivo sample of a low-grade glioma resection margin, SM-OCT is able to resolve the brain tumor margin. Based on these findings, SM-OCT represents a novel approach for intraoperative tumor margin detection and in vivo neuroimaging.

DeepLSR: a deep learning approach for laser speckle reduction

Speckle artifacts degrade image quality in virtually all modalities that utilize coherent energy, including optical coherence tomography, reflectance confocal microscopy, ultrasound, and widefield imaging with laser illumination. We present an adversarial deep learning framework for laser speckle reduction, called DeepLSR (https://durr.jhu.edu/DeepLSR), that transforms images from a source domain of coherent illumination to a target domain of speckle-free, incoherent illumination. We apply this method to widefield images of objects and tissues illuminated with a multi-wavelength laser, using light emitting diode-illuminated images as ground truth. In images of gastrointestinal tissues, DeepLSR reduces laser speckle noise by 6.4 dB, compared to a 2.9 dB reduction from optimized non-local means processing, a 3.0 dB reduction from BM3D, and a 3.7 dB reduction from an optical speckle reducer utilizing an oscillating diffuser. Further, DeepLSR can be combined with optical speckle reduction to reduce speckle noise by 9.4 dB. This dramatic reduction in speckle noise may enable the use of coherent light sources in applications that require small illumination sources and high-quality imaging, including medical endoscopy.

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.

2D MEMS-based high-speed beam-shifting technique for speckle noise reduction and flow rate measurement in optical coherence tomography

In this manuscript, a two-dimensional (2D) micro-electro-mechanical system (MEMS)-based, high-speed beam-shifting spectral domain optical coherence tomography (MHB-SDOCT) is proposed for speckle noise reduction and absolute flow rate measurement. By combining a zigzag scanning protocol, the frame rates of 45.2 Hz for speckle reduction and 25.6 Hz for flow rate measurement are achieved for in-vivo tissue imaging. Phantom experimental results have shown that by setting the incident beam angle to ϕ = 4.76° (between optical axis of objective lens and beam axis) and rotating the beam about the optical axis in 17 discrete angular positions, 91% of speckle noise in the structural images can be reduced. Furthermore, a precision of 0.0032 µl/s is achieved for flow rate measurement with the same beam angle, using three discrete angular positions around the optical axis. In-vivo experiments on human skin and chicken embryo were also implemented to further verify the performance of speckle noise reduction and flow rate measurement of MHB-SDOCT.

Real-Time Detection of Circulating Tumor Cells in Living Animals Using Functionalized Large Gold Nanorods

Optical coherence tomography (OCT) can be utilized with significant speckle reduction techniques and highly scattering contrast agents for non-invasive, contrast-enhanced imaging of living tissues at the cellular scale. The advantages of reduced speckle noise and improved targeted contrast can be harnessed to track objects as small as 2 μm in vivo, which enables applications for cell tracking and quantification in living subjects. Here we demonstrate the use of large gold nanorods as contrast agents for detecting individual micron-sized polystyrene beads and single myeloma cells in blood circulation using speckle-modulating OCT. This report marks the first time that OCT has been used to detect individual cells within blood in vivo. This technical capability unlocks exciting opportunities for dynamic detection and quantification of tumor cells circulating in living subjects.

Spatiotemporal optical coherence (STOC) manipulation suppresses coherent cross-talk in full-field swept-source optical coherence tomography

Full-field swept-source optical coherence tomography (FF-SS-OCT) provides high-resolution depth-resolved images of the sample by parallel Fourier-domain interferometric detection. Although FF-SS-OCT implements high-speed volumetric imaging, it suffers from the cross-talk-generated noise from spatially coherent lasers. This noise reduces the transversal image resolution, which in turn, limits the wide adaptation of FF-SS-OCT for practical and clinical applications. Here, we introduce the novel spatiotemporal optical coherence (STOC) manipulation. In STOC the time-varying inhomogeneous phase masks are used to modulate the light incident on the sample. By properly adjusting these phase masks, the spatial coherence can be reduced. Consequently, the cross-talk-generated noise is suppressed, the transversal image resolution is improved by the factor of 2 , and sample features become visible. STOC approach is validated by imaging 1951 USAF resolution test chart covered by the diffuser, scattering phantom and the rat skin ex vivo. In all these cases STOC suppresses the cross-talk-generated noise, and importantly, do not compromise the transversal resolution. Thus, our method provides an enhancement of FF-SS-OCT that can be beneficial for imaging biological samples.

Regularized pseudo-phase imaging for inspecting and sensing nanoscale features

Recovering tiny nanoscale features using a general optical imaging system is challenging because of poor signal to noise ratio. Rayleigh scattering implies that the detectable signal of an object of size d illuminated by light of wavelength λ is proportional to d⁶/λ⁴, which may be several orders of magnitude weaker than that of additive and multiplicative perturbations in the background. In this article, we solve this fundamental issue by introducing the regularized pseudo-phase, an observation quantity for polychromatic visible light microscopy that seems to be more sensitive than conventional intensity images for characterizing nanoscale features. We achieve a significant improvement in signal to noise ratio without making any changes to the imaging hardware. In addition, this framework not only retains the advantages of conventional denoising techniques, but also endows this new measurand (i.e., the pseudo-phase) with an explicit physical meaning analogous to optical phase. Experiments on a NIST reference material 8820 sample demonstrate that we can measure nanoscale defects, minute amounts of tilt in patterned samples, and severely noise-polluted nanostructure profiles with the pseudo-phase framework even when using a low-cost bright-field microscope.

Aperture phase modulation with adaptive optics: a novel approach for speckle reduction and structure extraction in optical coherence tomography

Speckle is an inevitable consequence of the use of coherent light in imaging and acts as noise that corrupts image formation in most applications. Optical coherence tomographic imaging, as a technique employing coherence time gating, suffers from speckle. We present here a novel method of suppressing speckle noise intrinsically compatible with adaptive optics (AO) for confocal coherent imaging: modulation of the phase in the system pupil aperture with a segmented deformable mirror (DM) to introduce minor perturbations in the point spread function. This approach creates uncorrelated speckle patterns in a series of images, enabling averaging to suppress speckle noise while maintaining structural detail. A method is presented that efficiently determines the optimal range of modulation of DM segments relative to their AO-optimized position so that speckle noise is reduced while image resolution and signal strength are preserved. The method is active and independent of sample properties. Its effectiveness and efficiency are quantified and demonstrated by both ex vivo non-biological and in vivo biological applications.

Optimization of the Trade-Off Between Speckle Reduction and Axial Resolution in Frequency Compounding

We measured the reduction of speckle by frequency compounding using Gaussian pulses, which have the least time-bandwidth product. The experimental results obtained from a tissue mimicking phantom agree quantitatively with numerical simulations of randomly distributed point scatterers. For a fixed axial resolution, the amount of speckle reduction is found to approach a maximum as the number of bands increases while the total spectral range that they cover is kept constant. An analytical solution of the maximal speckle reduction is derived and shows that the maximum improves approximately as the inverse square root of the Gaussian pulse bandwidth. Since the axial resolution is proportional to the inverse of the pulse bandwidth, an optimized trade-off between speckle reduction and axial resolution is obtained. Considerations for the applications of the optimized trade-off are discussed.

Super-resolution localization photoacoustic microscopy using intrinsic red blood cells as contrast absorbers

Photoacoustic microscopy (PAM) has become a premier microscopy tool that can provide the anatomical, functional, and molecular information of animals and humans in vivo. However, conventional PAM systems suffer from limited temporal and/or spatial resolution. Here, we present a fast PAM system and an agent-free localization method based on a stable and commercial galvanometer scanner with a custom-made scanning mirror (L-PAM-GS). This novel hardware implementation enhances the temporal resolution significantly while maintaining a high signal-to-noise ratio (SNR). These improvements allow us to photoacoustically and noninvasively observe the microvasculatures of small animals and humans in vivo. Furthermore, the functional hemodynamics, namely, the blood flow rate in the microvasculature, is successfully monitored and quantified in vivo. More importantly, thanks to the high SNR and fast B-mode rate (500 Hz), by localizing photoacoustic signals from captured red blood cells without any contrast agent, unresolved microvessels are clearly distinguished, and the spatial resolution is improved by a factor of 2.5 in vivo. L-PAM-GS has great potential in various fields, such as neurology, oncology, and pathology.

Frequency-Shifted Optical Feedback Measurement Technologies Using a Solid-State Microchip Laser

Since its first application toward displacement measurements in the early-1960s, laser feedback interferometry has become a fast-developing precision measurement modality with many kinds of lasers. By employing the frequency-shifted optical feedback, microchip laser feedback interferometry has been widely researched due to its advantages of high sensitivity, simple structure, and easy alignment. More recently, the laser confocal feedback tomography has been proposed, which combines the high sensitivity of laser frequency-shifted feedback effect and the axial positioning ability of confocal microscopy. In this paper, the principles of a laser frequency-shifted optical feedback interferometer and laser confocal feedback tomography are briefly introduced. Then we describe their applications in various kinds of metrology regarding displacement measurement, vibration measurement, physical quantities measurement, imaging, profilometry, microstructure measurement, and so on. Finally, the existing challenges and promising future directions are discussed.

Beam-shifting technique for speckle reduction and flow rate measurement in optical coherence tomography

In this Letter, we propose a beam-shifting optical coherence tomography scheme for speckle reduction and blood flow rate calculation, where variations of the speckle pattern and Doppler angle were generated by parallel shifting of the sample beam incident on the objective lens. The resultant optical coherent tomography images could then be averaged for speckle noise reduction and simultaneously analyzed for flow rate measurement. The performance of the proposed technique was verified by both phantom and in vivo experiments.

Decoherence of fiber supercontinuum light source for speckle-free imaging

Speckle-free imaging is attractive in laser-illuminated imaging systems. The evolutionary process of supercontinuum decoherence in extra-large mode area step-index multimode fiber is analyzed to provide high-quality broadband light source for speckle-free imaging. It is found that spectral bandwidth, number of spatial transverse modes, and decoherence among different modes all greatly contribute to speckle reduction. The combination of supercontinuum and extra-large mode area step-index multimode fiber can considerably increase the efficiency of decoherence process for speckle-free imaging. This work may enrich the research of speckle-free imaging and also provide guidance on speckle-free imaging using fiber-optics based light source.

Aberration-diverse optical coherence tomography for suppression of multiple scattering and speckle

Multiple scattering is a major barrier that limits the optical imaging depth in scattering media. In order to alleviate this effect, we demonstrate aberration-diverse optical coherence tomography (AD-OCT), which exploits the phase correlation between the deterministic signals from single-scattered photons to suppress the random background caused by multiple scattering and speckle. AD-OCT illuminates the sample volume with diverse aberrated point spread functions, and computationally removes these intentionally applied aberrations. After accumulating 12 astigmatism-diverse OCT volumes, we show a 10 dB enhancement in signal-to-background ratio via a coherent average of reconstructed signals from a USAF target located 7.2 scattering mean free paths below a thick scattering layer, and a 3× speckle contrast reduction from an incoherent average of reconstructed signals inside the scattering layer. This AD-OCT method, when implemented using astigmatic illumination, is a promising approach for ultra-deep volumetric optical coherence microscopy.

Planar Diffractive Lenses: Fundamentals, Functionalities, and Applications

Traditional objective lenses in modern microscopy, based on the refraction of light, are restricted by the Rayleigh diffraction limit. The existing methods to overcome this limit can be categorized into near-field (e.g., scanning near-field optical microscopy, superlens, microsphere lens) and far-field (e.g., stimulated emission depletion microscopy, photoactivated localization microscopy, stochastic optical reconstruction microscopy) approaches. However, they either operate in the challenging near-field mode or there is the need to label samples in biology. Recently, through manipulation of the diffraction of light with binary masks or gradient metasurfaces, some miniaturized and planar lenses have been reported with intriguing functionalities such as ultrahigh numerical aperture, large depth of focus, and subdiffraction-limit focusing in far-field, which provides a viable solution for the label-free superresolution imaging. Here, the recent advances in planar diffractive lenses (PDLs) are reviewed from a united theoretical account on diffraction-based focusing optics, and the underlying physics of nanofocusing via constructive or destructive interference is revealed. Various approaches of realizing PDLs are introduced in terms of their unique performances and interpreted by using optical aberration theory. Furthermore, a detailed tutorial about applying these planar lenses in nanoimaging is provided, followed by an outlook regarding future development toward practical applications.

Real-time speckle reduction in optical coherence tomography using the dual window method

Speckle is an intrinsic noise of interferometric signals which reduces contrast and degrades the quality of optical coherence tomography (OCT) images. Here, we present a frequency compounding speckle reduction technique using the dual window (DW) method. Using the DW method, speckle noise is reduced without the need to acquire multiple frames. A ~25% improvement in the contrast-to-noise ratio (CNR) was achieved using the DW speckle reduction method with only minimal loss (~17%) in axial resolution. We also demonstrate that real-time speckle reduction can be achieved at a B-scan rate of ~21 frames per second using a graphic processing unit (GPU). The DW speckle reduction technique can work on any existing OCT instrument without further system modification or extra components. This makes it applicable both in real-time imaging systems and during post-processing.

Visible-light optical coherence tomography: a review

Visible-light optical coherence tomography (vis-OCT) is an emerging imaging modality, providing new capabilities in both anatomical and functional imaging of biological tissue. It relies on visible light illumination, whereas most commercial and investigational OCTs use near-infrared light. As a result, vis-OCT requires different considerations in engineering design and implementation but brings unique potential benefits to both fundamental research and clinical care of several diseases. Here, we intend to provide a summary of the development of vis-OCT and its demonstrated applications. We also provide perspectives on future technology improvement and applications.