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

Coaxial Bright and Dark Field Optical Coherence Tomography

To improve the signal collection efficiency of Optical Coherence Tomography (OCT) for biomedical applications. A novel coaxial optical design was implemented, utilizing a wavefront-division beam splitter in the sample arm with a 45-degree rod mirror. This design allowed for the simultaneous collection of bright and dark field signals. The bright field signal was detected within its circular aperture in a manner similar to standard OCT, while the dark field signal passed through an annular-shaped aperture and was collected by the same spectrometer via a fiber array. This new configuration improved the signal collection efficiency by ∼3 dB for typical biological tissues. Dark-field OCT images were found to provide higher resolution, contrast and distinct information compared to standard bright-field OCT. By compounding bright and dark field images, speckle noise was suppressed by ∼ √2 . These advantages were validated using Teflon phantoms, chicken breast ex vivo, and human skin in vivo. This new OCT configuration significantly enhances signal collection efficiency and image quality, offering great potential for improving OCT technology with better depth, contrast, resolution, speckles, and signal-to-noise ratio. We believe that the bright and dark field signals will enable more comprehensive tissue characterization with the angled scattered light. This advancement will greatly promote the OCT technology in various clinical and biomedical research applications.

Multi-window approach enables two-fold improvement in OCT axial resolution with strong side-lobe suppression and improved phase sensitivity

A common processing approach for optical coherence tomography (OCT) uses a window function (e.g., Hann or rectangular window) for spectral shaping prior to calculating the Fourier transform. Here we build on a multi-window approach [Opt. Express8, 5267 (2017)10.1364/BOE.8.005267] that enables improved resolution while still suppressing side-lobe intensity. The shape of the window function defines the trade-off between main-lobe width (resolution) and side-lobe intensity. We have extended the approach to include the interferometric phase for phase-sensitive applications like vibrometry and Doppler OCT. Using the Hann window as a reference, we show that 11 Taylor windows are sufficient to achieve 50% improvement in axial resolution, -31 dB side-lobe intensity, and 20% improvement in phase sensitivity with low computational cost.

Optical coherence tomography image despeckling based on tensor singular value decomposition and fractional edge detection

Optical coherence tomography (OCT) imaging is a technique that is frequently used to diagnose medical conditions. However, coherent noise, sometimes referred to as speckle noise, can dramatically reduce the quality of OCT images, which has an adverse effect on how OCT images are used. In order to enhance the quality of OCT images, a speckle noise reduction technique is developed, and this method is modelled as a low-rank tensor approximation issue. The grouped 3D tensors are first transformed into the transform domain using tensor singular value decomposition (t-SVD). Then, to cut down on speckle noise, transform coefficients are thresholded. Finally, the inverse transform can be used to produce images with speckle suppression. To further enhance the despeckling results, a feature-guided thresholding approach based on fractional edge detection and an adaptive backward projection technique are also presented. Experimental results indicate that the presented algorithm outperforms several comparison methods in relation to speckle suppression, objective metrics, and edge preservation.

Corneal imaging with blue-light optical coherence microscopy

Corneal imaging is important for the diagnostic and therapeutic evaluation of many eye diseases. Optical coherence tomography (OCT) is extensively used in ocular imaging due to its non-invasive and high-resolution volumetric imaging characteristics. Optical coherence microscopy (OCM) is a technical variation of OCT that can image the cornea with cellular resolution. Here, we demonstrate a blue-light OCM as a low-cost and easily reproducible system to visualize corneal cellular structures such as epithelial cells, endothelial cells, keratocytes, and collagen bundles within stromal lamellae. Our blue-light OCM system achieved an axial resolution of 12 µm in tissue over a 1.2 mm imaging depth, and a lateral resolution of 1.6 µm over a field of view of 750 µm × 750 µm.

Denoising algorithm of OCT images via sparse representation based on noise estimation and global dictionary

Optical coherence tomography (OCT) is a high-resolution and non-invasive optical imaging technology, which is widely used in many fields. Nevertheless, OCT images are disturbed by speckle noise due to the low-coherent interference properties of light, resulting in significant degradation of OCT image quality. Therefore, a denoising algorithm of OCT images via sparse representation based on noise estimation and global dictionary is proposed in this paper. To remove noise and improve image quality, the algorithm first constructs a global dictionary from high-quality OCT images as training samples and then estimates the noise intensity for each input image. Finally, the OCT images are sparsely decomposed and reconstructed according to the global dictionary and noise intensity. Experimental results indicate that the proposed algorithm efficiently removes speckle noise from OCT images and yield high-quality images. The denoising effect and execution efficiency are evaluated based on quantitative metrics and running time, respectively. Compared with the mainstream adaptive dictionary denoising algorithm in sparse representation and other denoising algorithms, the proposed algorithm exhibits satisfying results in terms of speckle-noise reduction as well as edge preservation, at a reduced computational cost. Moreover, the final denoising effect is significantly better for sets of images with significant variations in noise intensity.

Deep imaging with 1.3 µm dual-axis optical coherence tomography and an enhanced depth of focus

For many clinical applications, such as dermatology, optical coherence tomography (OCT) suffers from limited penetration depth due primarily to the highly scattering nature of biological tissues. Here, we present a novel implementation of dual-axis optical coherence tomography (DA-OCT) that offers improved depth penetration in skin imaging at 1.3 µm compared to conventional OCT. Several unique aspects of DA-OCT are examined here, including the requirements for scattering properties to realize the improvement and the limited depth of focus (DOF) inherent to the technique. To overcome this limitation, our approach uses a tunable lens to coordinate focal plane selection with image acquisition to create an enhanced DOF for DA-OCT. This improvement in penetration depth is quantified experimentally against conventional on-axis OCT using tissue phantoms and mouse skin. The results presented here suggest the potential use of DA-OCT in situations where a high degree of scattering limits depth penetration in OCT imaging.

Statistical analysis of corneal OCT speckle: a non-parametric approach

In biomedical optics, it is often of interest to statistically model the amplitude of the speckle using some distributional approximations with their parameters acting as biomarkers. In this paper, a paradigm shift is being advocated in which non-parametric approaches are used. Specifically, a range of distances, evaluated in different domains, between an empirical non-parametric distribution of the normalized speckle amplitude sample and the benchmark Rayleigh distribution, is considered. Using OCT images from phantoms, two ex-vivo experiments with porcine corneas and an in-vivo experiment with human corneas, an evidence is provided that the non-parametric approach, despite its simplicity, could lead to equivalent or better results than the parametric approaches with distributional approximations. Concluding, in practice, the non-parametric approach should be considered as the first choice to speckle modeling before a particular distributional approximation is utilized.

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.

Self-fusion for OCT noise reduction

Reducing speckle noise is an important task for improving visual and automated assessment of retinal OCT images. Traditional image/signal processing methods only offer moderate speckle reduction; deep learning methods can be more effective but require substantial training data, which may not be readily available. We present a novel self-fusion method that offers effective speckle reduction comparable to deep learning methods, but without any external training data. We present qualitative and quantitative results in a variety of datasets from fovea and optic nerve head regions, with varying SNR values for input images.

Selective retinex enhancement based on the clustering algorithm and block-matching 3D for optical coherence tomography images

It is important to enhance the contrast and remove the speckle noise for optical coherence tomography (OCT) images. In this paper, we propose a selective retinex enhancement method based on the fuzzy c-means (FCM) clustering algorithm to enhance only the structure part in OCT images and combines with the block-matching 3D (BM3D) algorithm for filtering. In the proposed selective retinex enhancement method, we first calculate the feature image of the original image, which includes the mean value and standard deviation of each pixel in the original image and its correlation image. Second, by applying the FCM clustering algorithm to the feature image, a mask is generated that can distinguish the structure part from the background part in the OCT image. Then, the mask is applied to the multi-scale retinex algorithm, and only the structure part in the OCT image is enhanced. Moreover, the BM3D method is applied to filter the enhanced image. Experimental results demonstrate that the proposed method performs impressively in improving the contrast and removing the speckle noise of OCT images, and it provides better quantitative performance in terms of signal-to-noise ratio, contrast-to-noise ratio, equivalent number of looks, and the edge preservation parameter $ \beta $β.

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.

BM3D-based total variation algorithm for speckle removal with structure-preserving in OCT images

In this paper, we propose a total variation based on block matching 3D (BM3D-TV method), which includes the total variation regular term, the data fidelity term, and the block matching term. In addition, we also propose a fast numerical algorithm based on the split Bregman iteration for the proposed method. By assigning suitable weights to the data fidelity term and block matching term, the image noise reduction and the image structural characteristics can be matched optimally. We test the proposed method on six human retinal and one mouse skin optical coherence tomography (OCT) images respectively, and also compare it with total variation (TV) and BM3D, which were proved to be effective in denoising. The performances of these methods are quantitatively evaluated in terms of the signal-to-noise ratio, the contrast-to-noise ratio, and the averaged equivalent number of homogeneous areas at the aspects of speckle reduction and structure protection. Vast experiments show that the BM3D-TV method can effectively reduce speckle noise in OCT images, protect important structural information and improve image quality, compared with the BM3D and TV methods.

First Clinical Application of Low-Cost OCT

Purpose

We present the design of a new low-cost optical coherence tomography (OCT) system and compare its retinal imaging capabilities to a standard commercial system through a clinical study.

Methods

A spectral-domain OCT system was designed using various cost-reduction techniques to be low-cost, highly portable, and completely stand-alone. Clinical imaging was performed on 120 eyes of 60 patients (60 eyes of normal volunteers and 60 eyes with retinal disease) using both the low-cost OCT and a Heidelberg Engineering Spectralis OCT. Contrast-to-noise ratio (CNR) was measured from resulting images to determine system performance.

Results

The low-cost OCT system was successfully applied to clinical imaging of the retina. The system offers an axial resolution of 8.0 μm, a lateral resolution of 19.6 μm, and an imaging depth of 2.7 mm for a 6.6-mm field of view in the X and Y directions. Total cost is $5037, a significant size reduction compared to current commercial higher performance systems. Mean CNR value of low-cost OCT images is only 5.6% lower compared to the Heidelberg Spectralis.

Conclusions

The images captured with the low-cost OCT were of adequate resolution and allowed for clinical diagnostics. It offers comparable performance as a retinal screening tool at a fraction of the cost of current commercial systems.

Translational Relevance

Low-cost OCT has the potential to increase access to retinal imaging.

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.