Signal averaging improves signal-to-noise in OCT images: But which approach works best, and when?

Optical-coherence-tomography-based deep-learning scatterer-density estimator using physically accurate noise model

We demonstrate a deep-learning-based scatterer density estimator (SDE) that processes local speckle patterns of optical coherence tomography (OCT) images and estimates the scatterer density behind each speckle pattern. The SDE is trained using large quantities of numerically simulated OCT images and their associated scatterer densities. The numerical simulation uses a noise model that incorporates the spatial properties of three types of noise, i.e., shot noise, relative-intensity noise, and non-optical noise. The SDE's performance was evaluated numerically and experimentally using two types of scattering phantom and in vitro tumor spheroids. The results confirmed that the SDE estimates scatterer densities accurately. The estimation accuracy improved significantly when compared with our previous deep-learning-based SDE, which was trained using numerical speckle patterns generated from a noise model that did not account for the spatial properties of noise.

Acetazolamide Challenge Changes Outer Retina Bioenergy-Linked and Anatomical OCT Biomarkers Depending on Mouse Strain

Purpose

The purpose of this study was to test the hypothesis that optical coherence tomography (OCT) bioenergy-linked and anatomical biomarkers are responsive to an acetazolamide (ACZ) provocation.

Methods

C57BL/6J mice (B6J, a strain with relatively inefficient mitochondria) and 129S6/ev mice (S6, a strain with relatively efficient mitochondria) were given a single IP injection of ACZ (carbonic anhydrase inhibitor) or vehicle. In each mouse, the Mitochondrial Configuration within Photoreceptors based on the profile shape Aspect Ratio (MCP/AR) index was determined from the hyper-reflective band immediately posterior to the external limiting membrane (ELM). In addition, we tested for ACZ-induced acidification by measuring contraction of the external limiting membrane-retinal pigment epithelium (ELM-RPE) thickness; the hyporeflective band (HB) signal intensity at the photoreceptor tips was also examined. Finally, the nuclear layer thickness was measured.

Results

In response to ACZ, MCP/AR was greater-than-vehicle in B6J mice and lower-than-vehicle in S6 mice. ACZ-treated B6J and S6 mice both showed ELM-RPE contraction compared to vehicle-treated mice, consistent with dehydration in response to subretinal space acidification. The HB intensity at the photoreceptor tips and the outer nuclear layer thickness (B6J and S6), as well as the inner nuclear layer thickness of B6J mice, were all lower than vehicle following ACZ.

Conclusions

Photoreceptor respiratory efficacy can be evaluated in vivo based on distinct rod mitochondria responses to subretinal space acidification measured with OCT biomarkers and an ACZ challenge, supporting and extending our previous findings measured with light-dark conditions.

Polarization-artifact reduction and accuracy improvement of Jones-matrix polarization-sensitive optical coherence tomography by multi-focus-averaging based multiple scattering reduction

Polarization-sensitive optical coherence tomography (PS-OCT) is a promising biomedical imaging tool for the differentiation of various tissue properties. However, the presence of multiple-scattering (MS) signals can degrade the quantitative polarization measurement accuracy. We demonstrate a method to reduce MS signals and increase the measurement accuracy of Jones matrix PS-OCT. This method suppresses MS signals by averaging multiple Jones matrix volumes measured using different focal positions. The MS signals are decorrelated among the volumes by focus position modulation and are thus reduced by averaging. However, the single scattering signals are kept consistent among the focus-modulated volumes by computational refocusing. We validated the proposed method using a scattering phantom and a postmortem medaka fish. The results showed reduced artifacts in birefringence and degree-of-polarization uniformity measurements, particularly in deeper regions in the samples. This method offers a practical solution to mitigate MS-induced artifacts in PS-OCT imaging and improves quantitative polarization measurement accuracy.

Speckle contrast reduction through the use of a modally-specific photonic lantern for optical coherence tomography

A few-mode optical coherence tomography (FM-OCT) system was developed around a 2 × 1 modally-specific photonic lantern (MSPL) centered at 1310 nm. The MSPL allowed FM-OCT to acquire two coregistered images with uncorrelated speckle patterns generated by their specific coherent spread function. Here, we showed that averaging such images in vitro and in vivo reduced the speckle contrast by up to 28% and increased signal-to-noise ratio (SNR) by up to 48% with negligible impact on image spatial resolution. This method is compatible with other speckle reduction techniques to further improve OCT image quality.

A hand-held optical coherence tomography angiography scanner based on angiography reconstruction transformer networks

Optical coherence tomography angiography (OCTA) has successfully demonstrated its viability for clinical applications in dermatology. Due to the high optical scattering property of skin, extracting high-quality OCTA images from skin tissues requires at least six-repeated scans. While the motion artifacts from the patient and the free hand-held probe can lead to a low-quality OCTA image. Our deep-learning-based scan pipeline enables fast and high-quality OCTA imaging with 0.3-s data acquisition. We utilize a fast scanning protocol with a 60 μm/pixel spatial interval rate and introduce angiography-reconstruction-transformer (ART) for 4× super-resolution of low transverse resolution OCTA images. The ART outperforms state-of-the-art networks in OCTA image super-resolution and provides a lighter network size. ART can restore microvessels while reducing the processing time by 85%, and maintaining improvements in structural similarity and peak-signal-to-noise ratio. This study represents that ART can achieve fast and flexible skin OCTA imaging while maintaining image quality.

Ultra-high-resolution optical coherence tomography for the investigation of thin multilayered pharmaceutical coatings

Optical Coherence Tomography (OCT) has recently gained attention as a promising technology for in-line monitoring of pharmaceutical film-coating processes for (single-layered) tablet coatings and end-point detection with commercial systems. An increasing interest in the investigation of multiparticulate dosage forms with mostly multi-layered coatings below 20 µm final film thickness demands advancement in OCT technology for pharmaceutical imaging. We present an ultra-high-resolution (UHR-) OCT and investigate its performance based on three different multiparticulate dosage forms with different layer structures (one single-layered, two multi-layered) with layer thicknesses in a range from 5 to 50 µm. The achieved system resolution of 2.4 µm (axial) and 3.4 µm (lateral, both in air) enables the assessment of defects, film thickness variability and morphological features within the coating, previously unattainable using OCT. Despite the high transverse resolution, the provided depth of field was found sufficient to reach the core region of all dosage forms under test. We further demonstrate an automated segmentation and evaluation of UHR-OCT images for coating thicknesses, where human experts struggle using today's standard OCT systems.

Fast optical coherence tomography angiography image acquisition and reconstruction pipeline for skin application

Traditional high-quality OCTA images require multi-repeated scans (e.g., 4-8 repeats) in the same position, which may cause the patient to be uncomfortable. We propose a deep-learning-based pipeline that can extract high-quality OCTA images from only two-repeat OCT scans. The performance of the proposed image reconstruction U-Net (IRU-Net) outperforms the state-of-the-art UNet vision transformer and UNet in OCTA image reconstruction from a two-repeat OCT signal. The results demonstrated a mean peak-signal-to-noise ratio increased from 15.7 to 24.2; the mean structural similarity index measure improved from 0.28 to 0.59, while the OCT data acquisition time was reduced from 21 seconds to 3.5 seconds (reduced by 83%).

Deep-Learning-Based Fast Optical Coherence Tomography (OCT) Image Denoising for Smart Laser Osteotomy

Laser osteotomy promises precise cutting and minor bone tissue damage. We proposed Optical Coherence Tomography (OCT) to monitor the ablation process toward our smart laser osteotomy approach. The OCT image is helpful to identify tissue type and provide feedback for the ablation laser to avoid critical tissues such as bone marrow and nerve. Furthermore, in the implementation, the tissue classifier's accuracy is dependent on the quality of the OCT image. Therefore, image denoising plays an important role in having an accurate feedback system. A common OCT image denoising technique is the frame-averaging method. Inherent to this method is the need for multiple images, i.e., the more images used, the better the resulting image quality. However, this approach comes at the price of increased acquisition time and sensitivity to motion artifacts. To overcome these limitations, we applied a deep-learning denoising method capable of imitating the frame-averaging method. The resulting image had a similar image quality to the frame-averaging and was better than the classical digital filtering methods. We also evaluated if this method affects the tissue classifier model's accuracy that will provide feedback to the ablation laser. We found that image denoising significantly increased the accuracy of the tissue classifier. Furthermore, we observed that the classifier trained using the deep learning denoised images achieved similar accuracy to the classifier trained using frame-averaged images. The results suggest the possibility of using the deep learning method as a pre-processing step for real-time tissue classification in smart laser osteotomy.

Precision of attenuation coefficient measurements by optical coherence tomography

SIGNIFICANCE

Optical coherence tomography (OCT) is an interferometric imaging modality, which provides tomographic information on the microscopic scale. Furthermore, OCT signal analysis facilitates quantification of tissue optical properties (e.g., the attenuation coefficient), which provides information regarding the structure and organization of tissue. However, a rigorous and standardized measure of the precision of the OCT-derived optical properties, to date, is missing.

AIM

We present a robust theoretical framework, which provides the Cramér -Rao lower bound σμOCT for the precision of OCT-derived optical attenuation coefficients.

APPROACH

Using a maximum likelihood approach and Fisher information, we derive an analytical solution for σμOCT when the position and depth of focus are known. We validate this solution, using simulated OCT signals, for which attenuation coefficients are extracted using a least-squares fitting procedure.

RESULTS

Our analytical solution is in perfect agreement with simulated data without shot noise. When shot noise is present, we show that the analytical solution still holds for signal-to-noise ratios (SNRs) in the fitting window being above 20 dB. For other cases (SNR<20 dB, focus position not precisely known), we show that the numerical calculation of the precision agrees with the σμOCT derived from simulated signals.

CONCLUSIONS

Our analytical solution provides a fast, rigorous, and easy-to-use measure for OCT-derived attenuation coefficients for signals above 20 dB. The effect of uncertainties in the focal point position on the precision in the attenuation coefficient, the second assumption underlying our analytical solution, is also investigated by numerical calculation of the lower bounds. This method can be straightforwardly extended to uncertainty in other system parameters.

High-Speed Balanced-Detection Visible-Light Optical Coherence Tomography in the Human Retina Using Subpixel Spectrometer Calibration

Increases in speed and sensitivity enabled rapid clinical adoption of optical coherence tomography (OCT) in ophthalmology. Recently, visible-light OCT (vis-OCT) achieved ultrahigh axial resolution, improved tissue contrast, and provided new functional imaging capabilities, demonstrating the potential to improve clinical care further. However, limited speed and sensitivity caused by the high relative intensity noise (RIN) in supercontinuum lasers impeded the clinical adoption of vis-OCT. To overcome these limitations, we developed balanced-detection vis-OCT (BD-vis-OCT), which uses two calibrated spectrometers to cancel RIN and other noises. We analyzed the RIN to achieve robust subpixel calibration between the two spectrometers and showed that BD-vis-OCT reduced the A-line noise floor by up to 20.5 dB. Metrics comparing signal-to-noise-ratios showed similar image qualities across multiple reference arm powers, a hallmark of operation near the shot-noise limit. We imaged healthy human retinas at an A-line rate of 125 kHz and a field-of-view up to 10 mm ×4 mm. We found that BD-vis-OCT revealed retinal anatomical features previously obscured by the noise floor.

Light-adapted flicker optoretinograms captured with a spatio-temporal optical coherence-tomography (STOC-T) system

For many years electroretinography (ERG) has been used for obtaining information about the retinal physiological function. More recently, a new technique called optoretinography (ORG) has been developed. In one form of this technique, the physiological response of retinal photoreceptors to visible light, resulting in a nanometric photoreceptor optical path length change, is measured by phase-sensitive optical coherence tomography (OCT). To date, a limited number of studies with phase-based ORG measured the retinal response to a flickering light stimulation. In this work, we use a spatio-temporal optical coherence tomography (STOC-T) system to capture optoretinograms with a flickering stimulus over a 1.7 × 0.85 mm² area of a light-adapted retina located between the fovea and the optic nerve. We show that we can detect statistically-significant differences in the photoreceptor optical path length (OPL) modulation amplitudes in response to different flicker frequencies and with better signal to noise ratios (SNRs) than for a dark-adapted eye. We also demonstrate the ability to spatially map such response to a patterned stimulus with light stripes flickering at different frequencies, highlighting the prospect of characterizing the spatially-resolved temporal-frequency response of the retina with ORG.

Analysis and reduction of noise-induced depolarization in catheter based polarization sensitive optical coherence tomography

In catheter based polarization sensitive optical coherence tomography (PS-OCT), a optical fiber with a rapid rotation in the catheter can cause low signal-to-noise ratio (SNR), polarization state instability, phase change of PS-OCT signals and then heavy noise-induced depolarization, which has a strong impact on the phase retardation measurement of the sample. In this paper, we analyze the noise-induced depolarization and find that the effect of depolarization can be reduced by polar decomposition after incoherent averaging in the Mueller matrix averaging (MMA) method. Namely, MMA can reduce impact of noise on phase retardation mapping. We present a Monte Carlo method based on PS-OCT to numerically describe noise-induced depolarization effect and contrast phase retardation imaging results by MMA and Jones matrix averaging (JMA) methods. The peak signal to noise ratio (PSNR) of simulated images processed by MMA is higher than about 8.9 dB than that processed by JMA. We also implement experiments of multiple biological tissues using the catheter based PS-OCT system. From the simulation and experimental results, we find the polarization contrasts processed by the MMA are better than those by JMA, especially at areas with high depolarization, because the MMA can reduce effect of noise-induced depolarization on the phase retardation measurement.

Fast and accurate spectral-estimation axial super-resolution optical coherence tomography

Spectral-estimation OCT (SE-OCT) is a computational method to enhance the axial resolution beyond the traditional bandwidth limit. However, it has not yet been used widely due to its high computational load, dependency on user-optimized parameters, and inaccuracy in intensity reconstruction. In this study, we implement SE-OCT using a fast implementation of the iterative adaptive approach (IAA). This non-parametric spectral estimation method is optimized for use on OCT data. Both in simulations and experiments we show an axial resolution improvement with a factor between 2 and 10 compared to standard discrete Fourier transform. Contrary to parametric methods, IAA gives consistent peak intensity and speckle statistics. Using a recursive and fast reconstruction scheme the computation time is brought to the sub-second level for a 2D scan. Our work shows that SE-OCT can be used for volumetric OCT imaging in a reasonable computation time, thus paving the way for wide-scale implementation of super-resolution OCT.

Time-domain signal averaging to improve microparticles detection and enumeration accuracy in a microfluidic impedance cytometer

Microfluidic impedance cytometry is a powerful system to measure micro and nano-sized particles and is routinely used in point-of-care disease diagnostics and other biomedical applications. However, small objects near a sensor's detection limit are plagued with relatively significant background noise and are difficult to identify for every case. While many data processing techniques can be utilized to reduce noise and improve signal quality, frequently they are still inadequate to push sensor detection limits. Here, we report the first demonstration of a novel signal averaging algorithm effective in noise reduction of microfluidic impedance cytometry data, improving enumeration accuracy, and reducing detection limits. Our device uses a 22 µm tall × 100 µm wide (with 30 µm wide focused aperture) microchannel and gold coplanar microelectrodes that generate an electric field, recording bipolar pulses from polystyrene microparticles flowing through the channel. In addition to outlining a modified moving signal averaging technique theoretically and with a model data set, we also performed a compendium of characterization experiments including variations in flow rate, input voltage, and particle size. Multivariate metrics from each experiment are compared including signal amplitude, pulse width, background noise, and signal-to-noise ratio (SNR). Incorporating our technique resulted in improved SNR and counting accuracy across all experiments conducted, and the limit of detection improved from 5 to 1 µm particles without modifying microchannel dimensions. Succeeding this, we envision implementing our modified moving average technique to develop next-generation microfluidic impedance cytometry devices with an expanded dynamic range and improved enumeration accuracy. This can be exceedingly useful for many biomedical applications, such as infectious disease diagnostics where devices may enumerate larger-scale immune cells alongside sub-micron bacterium in the same sample.

Resolution-enhanced OCT and expanded framework of information capacity and resolution in coherent imaging

Spatial resolution in conventional optical microscopy has traditionally been treated as a fixed parameter of the optical system. Here, we present an approach to enhance transverse resolution in beam-scanned optical coherence tomography (OCT) beyond its aberration-free resolution limit, without any modification to the optical system. Based on the theorem of invariance of information capacity, resolution-enhanced (RE)-OCT navigates the exchange of information between resolution and signal-to-noise ratio (SNR) by exploiting efficient noise suppression via coherent averaging and a simple computational bandwidth expansion procedure. We demonstrate a resolution enhancement of 1.5 × relative to the aberration-free limit while maintaining comparable SNR in silicone phantom. We show that RE-OCT can significantly enhance the visualization of fine microstructural features in collagen gel and ex vivo mouse brain. Beyond RE-OCT, our analysis in the spatial-frequency domain leads to an expanded framework of information capacity and resolution in coherent imaging that contributes new implications to the theory of coherent imaging. RE-OCT can be readily implemented on most OCT systems worldwide, immediately unlocking information that is beyond their current imaging capabilities, and so has the potential for widespread impact in the numerous areas in which OCT is utilized, including the basic sciences and translational medicine.

Phase-corrected buffer averaging for enhanced OCT angiography using FDML laser

Megahertz-rate optical coherence tomography angiography (OCTA) is highly anticipated as an ultrafast imaging tool in clinical settings. However, shot-noise-limited sensitivity is inevitably reduced in high-speed imaging systems. In this Letter, we present a coherent buffer averaging technique for use with a Fourier-domain mode-locked (FDML) laser to improve OCTA contrast at 1060 nm MHz-rate retinal imaging. Full characterization of spectral variations among the FDML buffers and a numerical correction method are also presented, with the results demonstrating a 10-fold increase in the phase alignment among buffers. Coherent buffer averaging provided better OCTA contrast than the conventional multi-frame averaging approach with a faster acquisition time.

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.

Improved accuracy of quantitative birefringence imaging by polarization sensitive OCT with simple noise correction and its application to neuroimaging

Polarization-sensitive optical coherence tomography (PS-OCT) enables three-dimensional imaging of biological tissues based on the inherent contrast provided by scattering and polarization properties. In fibrous tissue such as the white matter of the brain, PS-OCT allows quantitative mapping of tissue birefringence. For the popular PS-OCT layout using a single circular input state, birefringence measurements are based on a straight-forward evaluation of phase retardation data. However, the accuracy of these measurements strongly depends on the signal-to-noise ratio (SNR) and is prone to mapping artifacts when the SNR is low. Here we present a simple yet effective approach for improving the accuracy of PS-OCT phase retardation and birefringence measurements. By performing a noise bias correction of the detected OCT signal amplitudes, the impact of the noise floor on retardation measurements can be markedly reduced. We present simulation data to illustrate the influence of the noise bias correction on phase retardation measurements and support our analysis with real-world PS-OCT image data.

Model-based optical coherence tomography angiography enables motion-insensitive vascular imaging

We present a significant step toward ultrahigh-resolution, motion-insensitive characterization of vascular dynamics. Optical coherence tomography angiography (OCTA) is an invaluable diagnostic technology for non-invasive, label-free vascular imaging in vivo. However, since it relies on detecting moving cells from consecutive scans, high-resolution OCTA is susceptible to tissue motion, which imposes challenges in resolving and quantifying small vessels. We developed a novel OCTA technique named ultrahigh-resolution factor angiography (URFA) by modeling repeated scans as generative latent variables, with a common variance representing shared features and a unique variance representing motion. By iteratively maximizing the combined log-likelihood probability of these variances, the unique variance is largely separated. Meanwhile, features in the common variance are decoupled, in which vessels with dynamic flow are extracted from tissue structure by integrating high-order factors. Combined with Gabor-domain optical coherence microscopy, URFA successfully extracted high-resolution cutaneous vasculature despite severe involuntary tissue motion and scanner oscillation, significantly improving the visualization and characterization of micro-capillaries in vivo. Compared with the conventional approach, URFA reduces motion artifacts by nearly 50% on average, evaluated on local differences.

Analysis of the impact of optical aberrations in en-face full-field OCT microscopy

Optical coherence tomography (OCT) is a powerful technique for cross-sectioning imaging. However, the lateral resolution may be degraded by optical aberrations originating from the sample or the setup. We present an extensive quantitative study of the impact of aberrations in time-domain en-face full-field OCT (FFOCT). Using an adaptive optics loop integrated in an FFOCT setup, a deformable mirror is used to introduce low-order calibrated aberrations. The experimental analysis of both the line spread functions (SF) and the complex object images has allowed us to measure the loss in contrast and the impact on lateral spatial resolution. We demonstrate that the frequency content of FFOCT image spectra in terms of signal-to-noise ratio and cutoff frequency is degraded by aberrations but remains much higher than in conventional incoherent images. Line SF profiles in conventional imaging display widening, whereas in FFOCT they display oscillations, leading to the possible perception of preserved resolution. Nevertheless, for complex objects, the aberration image blurring is strong due to the convolution process by the point SF, resulting in a significant filtering of the image spatial spectrum.

Intrinsic spectrally-dependent background in spectroscopic visible-light optical coherence tomography

Visible-light optical coherence tomography (vis-OCT) has enabled new spectroscopic applications, such as retinal oximetry, as a result of increased optical absorption and scattering contacts in biological tissue and improved axial resolution. Besides extracting tissue properties from back-scattered light, spectroscopic analyses must consider spectral alterations induced by image reconstruction itself. We investigated an intrinsic spectral bias in the background noise floor, which is hereby referred to as the spectrally-dependent background (SDBG). We developed an analytical model to predict the SDBG-induced bias and validated this model using numerically simulated and experimentally acquired data. We found that SDBG systemically altered the measured spectra of blood in human retinal vessels in vis-OCT, as compared to literature data. We provided solutions to quantify and compensate for SDBG in retinal oximetry. This work is particularly significant for clinical applications of vis-OCT.

400 MHz ultrafast optical coherence tomography

An ultrafast time-stretched swept source with a sweep rate of 400 MHz is demonstrated based on the buffering of a 100 MHz femtosecond laser pulse train. To the best of our knowledge, this is the highest sweep rate of swept sources for optical coherence tomography (OCT) that has been reported. With a 10 dB sweep range of ∼100nm, an axial resolution of 19 µm is obtained in the OCT. OCT imaging of high-speed rotating disks is demonstrated. A composite complex apodization method is proposed and demonstrated to enhance the signal to noise ratio in the OCT imaging.

Quantification of plant morphology and leaf thickness with optical coherence tomography

Optical coherence tomography (OCT) can be a valuable imaging tool for in vivo and label-free digital plant phenotyping. However, for imaging leaves, air-filled cavities limit the penetration depth and reduce the image quality. Moreover, up to now quantification of leaf morphology with OCT has been done in one-dimensional or two-dimensional images only, and has often been limited to relative measurements. In this paper, we demonstrate a significant increase in OCT imaging depth and image quality by infiltrating the leaf air spaces with water. In the obtained high-quality OCT images the top and bottom surface of the leaf are digitally segmented. Moreover, high-quality en face images of the leaf are obtained from numerically flattened leaves. Segmentation in three-dimensional OCT images is used to quantify the spatially resolved leaf thickness. Based on a segmented leaf image, the refractive index of an infiltrated leaf is measured to be 1.345±0.004, deviating only 1.2% from that of pure water. Using the refractive index and a correction for refraction effects at the air-leaf interface, we quantitatively mapped the leaf thickness. The results show that OCT is an efficient and promising technique for quantitative phenotyping on leaf and tissue level.

Processing-Aware Real-Time Rendering for Optimized Tissue Visualization in Intraoperative 4D OCT

Intraoperative Optical Coherence Tomography (iOCT) has advanced in recent years to provide real-time high resolution volumetric imaging for ophthalmic surgery. It enables real-time 3D feedback during precise surgical maneuvers. Intraoperative 4D OCT generally exhibits lower signal-to-noise ratio compared to diagnostic OCT and visualization is complicated by instrument shadows occluding retinal tissue. Additional constraints of processing data rates upwards of 6GB/s create unique challenges for advanced visualization of 4D OCT. Prior approaches for real-time 4D iOCT rendering have been limited to applying simple denoising filters and colorization to improve visualization. We present a novel real-time rendering pipeline that provides enhanced intraoperative visualization and is specifically designed for the high data rates of 4D iOCT. We decompose the volume into a static part consisting of the retinal tissue and a dynamic part including the instrument. Aligning the static parts over time allows temporal compounding of these structures for improved image quality. We employ a translational motion model and use axial projection images to reduce the dimensionality of the alignment. A model-based instrument segmentation on the projections discriminates static from dynamic parts and is used to exclude instruments from the compounding. Our real-time rendering method combines the compounded static information with the latest iOCT data to provide a visualization which compensates instrument shadows and improves instrument visibility. We evaluate the individual parts of our pipeline on pre-recorded OCT volumes and demonstrate the effectiveness of our method on a recorded volume sequence with a moving retinal forceps.

Approaches to quantify optical coherence tomography angiography metrics

Optical coherence tomography (OCT) has revolutionized the field of ophthalmology in the last three decades. As an OCT extension, OCT angiography (OCTA) utilizes a fast OCT system to detect motion contrast in ocular tissue and provides a three-dimensional representation of the ocular vasculature in a non-invasive, dye-free manner. The first OCT machine equipped with OCTA function was approved by U.S. Food and Drug Administration in 2016 and now it is widely applied in clinics. To date, numerous methods have been developed to aid OCTA interpretation and quantification. In this review, we focused on the workflow of OCTA-based interpretation, beginning from the generation of the OCTA images using signal decorrelation, which we divided into intensity-based, phase-based and phasor-based methods. We further discussed methods used to address image artifacts that are commonly observed in clinical settings, to the algorithms for image enhancement, binarization, and OCTA metrics extraction. We believe a better grasp of these technical aspects of OCTA will enhance the understanding of the technology and its potential application in disease diagnosis and management. Moreover, future studies will also explore the use of ocular OCTA as a window to link ocular vasculature to the function of other organs such as the kidney and brain.

Computational aberration correction in spatiotemporal optical coherence (STOC) imaging

Spatiotemporal optical coherence (STOC) imaging is a new technique for suppressing coherent cross talk noise in Fourier-domain full-field optical coherence tomography (FD-FF-OCT). In STOC imaging, the time-varying inhomogeneous phase masks modulate the incident light to alter the interferometric signal. Resulting interference images are then processed as in standard FD-FF-OCT and averaged incoherently or coherently to produce cross-talk-free volumetric optical coherence tomography (OCT) images of the sample. Here, we show that coherent averaging is suitable when phase modulation is performed for both interferometer arms simultaneously. We explain the advantages of coherent over incoherent averaging. Specifically, we show that modulated signal, after coherent averaging, preserves lateral phase stability, enabling computational phase correction to compensate for geometrical aberrations. Ultimately, we employ it to correct for aberrations present in the image of the photoreceptor layer of the human retina that reveals otherwise invisible photoreceptor mosaics.

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.