Retinal cross-section motion correction in three-dimensional retinal optical coherence tomography

Motion correction is an important issue in ophthalmic optical coherence tomography (OCT), and can improve the ability of data sets to reflect the physiological structures of tissues and make visualization and subsequent analysis easier. In this study, we present a novel method to correct the cross-sectional motion artifacts in retinal OCT volumes. Motion along the x-direction (fast-scan direction) is corrected through the normalized cross-correlation algorithm, while axial motion compensation is performed using the polynomial fitting method on the inner segment/outer segment (IS/OS) layer segmented by the shortest path faster algorithm (SPFA). The results of volunteers with central serous chorioretinopathy demonstrate that the proposed method effectively corrects motion artifacts in OCT volumes and may have potential application value in the evaluation of ophthalmic diseases such as diabetic retinopathy, glaucoma and age-related macular degeneration.     

Comparative study of deep neural networks with unsupervised Noise2Noise strategy for noise reduction of optical coherence tomography images

As a powerful diagnostic tool, optical coherence tomography (OCT) has been widely used in various clinical setting. However, OCT images are susceptible to inherent speckle noise that may contaminate subtle structure information, due to low-coherence interferometric imaging procedure. Many supervised learning-based models have achieved impressive performance in reducing speckle noise of OCT images trained with a large number of noisy-clean paired OCT images, which are not commonly feasible in clinical practice. In this article, we conducted a comparative study to investigate the denoising performance of OCT images over different deep neural networks through an unsupervised Noise2Noise (N2N) strategy, which only trained with noisy OCT samples. Four representative network architectures including U-shaped model, multi-information stream model, straight-information stream model and GAN-based model were investigated on an OCT image dataset acquired from healthy human eyes. The results demonstrated all four unsupervised N2N models offered denoised OCT images with a performance comparable with that of supervised learning models, illustrating the effectiveness of unsupervised N2N models in denoising OCT images. Furthermore, U-shaped models and GAN-based models using UNet network as generator are two preferred and suitable architectures for reducing speckle noise of OCT images and preserving fine structure information of retinal layers under unsupervised N2N circumstances.     

Gingivitis resolution followed by optical coherence tomography and fluorescence imaging: A case study

Gingivitis is highly prevalent in adults, and if left untreated, can progress to periodontitis. In this article, we present an interesting case study where the resolution of gingivitis was followed over a period of 10 days using optical coherence tomography (OCT) and light-induced autofluorescence (LIAF). We demonstrate that OCT and its functional angiography can distinctively capture the changes during the resolution of gingivitis; while LIAF can detect red-fluorescent signals associated with mature plaque present at the inflamed site. The acute inflammatory region showed evidence of angiogenesis based on the quantification of vessel density and number; while no angiogenesis was detected within the less inflamed region. Gingival thickness showed a reduction of 140 ± 26 μm on average, measured between the peak gingivitis event and the period wherein the inflammation was resolved. Vessels in the angiogenesis site was found to reduce exponentially. The mildly inflamed site showed a decreasing trend in the vessel size, which however was within the error of the measurement.     

Phase unwrapping for Doppler spectral domain optical coherence tomography flow measurement

Doppler optical coherence tomography (OCT) offers additional flow velocity information, which extends the application of OCT. Phase wrapping is the inherent problem that limits measureable range of Doppler OCT. We propose a phase unwrapping method which is suitable for correcting phase in Doppler OCT images. Points (pixels) in flow region are divided into groups according to the radial distance. Points in the same group are supposed to have close velocity. Phase unwrapping algorithm begins at the boundary layer group and is performed sequentially toward the center. Using the proposed criterion, points in a group are separated into two categories, signal points and noise points. Wrapping rounds are determined for signal points phase unwrapping. Mean value of the corrected signal points replaces the noise points for noise reduction. The method is validated with capillary tube flow phantom and in vivo blood flow.     

Optical coherence hyperspectral microscopy with a single supercontinuum light source

In the paper, we have developed an optical coherence hyperspectral microscopy with a single supercontinuum light source. The microscopy consists of optical coherence tomography (OCT) and hyperspectral imaging (HSI), which can visualize the structural and functional characteristics of biological tissues. The 500 to 700 nm band is selected for HSI and OCT imaging, where HSI enables imaging of oxygen saturation and hemoglobin (Hb) content, while OCT acquires structural characteristics to assess the morphology of biological tissues. The system performance of the optical coherence hyperspectral microscopy is verified by normal mice ears, and the practical applications of the microscopy is further performed in 4T1 and inflammation Balb/c mice ears in vivo. The experimental results demonstrate that the microscopy has potential to provide complementary information for clinical applications.     

Preclinical mouse model of optical coherence tomography for subcortical brain imaging without dissection

The purpose of this study was to investigate the feasibility of using optical coherence tomography (OCT) to identify internal brain lesions, specifically intracerebral hemorrhage, without dissection. Mice with artificially injected brain hematomas were used to test the OCT system, and the recorded images were compared with microscopic images of the same mouse brains after hematoxylin and eosin staining. The intracranial structures surrounding the hematomas were clearly visualized by the OCT system without dissection. These images reflect the ability of OCT to determine the extent of a lesion in several planes. OCT is a useful technology, and these findings could be used as a starting point for future research in intraoperative imaging.     

N2NSR-OCT: Simultaneous denoising and super-resolution in optical coherence tomography images using semisupervised deep learning

Optical coherence tomography (OCT) imaging shows a significant potential in clinical routines due to its noninvasive property. However, the quality of OCT images is generally limited by inherent speckle noise of OCT imaging and low sampling rate. To obtain high signal-to-noise ratio (SNR) and high-resolution (HR) OCT images within a short scanning time, we presented a learning-based method to recover high-quality OCT images from noisy and low-resolution OCT images. We proposed a semisupervised learning approach named N2NSR-OCT, to generate denoised and super-resolved OCT images simultaneously using up- and down-sampling networks (U-Net (Semi) and DBPN (Semi)). Additionally, two different super-resolution and denoising models with different upscale factors (2× and 4× ) were trained to recover the high-quality OCT image of the corresponding down-sampling rates. The new semisupervised learning approach is able to achieve results comparable with those of supervised learning using up- and down-sampling networks, and can produce better performance than other related state-of-the-art methods in the aspects of maintaining subtle fine retinal structures.     

The use of optical coherence tomography and convolutional neural networks to distinguish normal and abnormal oral mucosa

Incomplete surgical resection of head and neck squamous cell carcinoma (HNSCC) is the most common cause of local HNSCC recurrence. Currently, surgeons rely on preoperative imaging, direct visualization, palpation and frozen section to determine the extent of tissue resection. It has been demonstrated that optical coherence tomography (OCT), a minimally invasive, nonionizing near infrared mesoscopic imaging modality can resolve subsurface differences between normal and abnormal head and neck mucosa. Previous work has utilized two‐dimensional OCT imaging which is limited to the evaluation of small regions of interest generated frame by frame. OCT technology is capable of performing rapid volumetric imaging, but the capacity and expertise to analyze this massive amount of image data is lacking. In this study, we evaluate the ability of a retrained convolutional neural network to classify three‐dimensional OCT images of head and neck mucosa to differentiate normal and abnormal tissues with sensitivity and specificity of 100% and 70%, respectively. This method has the potential to serve as a real‐time analytic tool in the assessment of surgical margins.     

Hyperspectral optical coherence tomography for in vivo visualization of melanin in the retinal pigment epithelium

Previous studies for melanin visualization in the retinal pigment epithelium (RPE) have exploited either its absorption properties (using photoacoustic tomography or photothermal optical coherence tomography [OCT]) or its depolarization properties (using polarization sensitive OCT). However, these methods are only suitable when the melanin concentration is sufficiently high. In this work, we present the concept of hyperspectral OCT for melanin visualization in the RPE when the concentration is low. Based on white light OCT, a hyperspectral stack of 27 wavelengths (440‐700 nm) was created in post‐processing for each depth‐resolved image. Owing to the size and shape of the melanin granules in the RPE, the variations in backscattering coefficient as a function of wavelength could be identified—a result which is to be expected from Mie theory. This effect was successfully identified both in eumelanin‐containing phantoms and in vivo in the low‐concentration Brown Norway rat RPE.      

Improving cerebral microvascular image quality of optical coherence tomography angiography with deep learning-based segmentation

Optical coherence tomography angiography (OCTA) can map the microvascular networks of the cerebral cortices with micrometer resolution and millimeter penetration. However, the high scattering of the skull and the strong noise in the deep imaging region will distort the vasculature projections and decrease the OCTA image quality. Here, we proposed a deep learning-based segmentation method based on a U-Net convolutional neural network to extract the cortical region from the OCT image. The vascular networks were then visualized by three OCTA algorithms. The image quality of the vasculature projections was assessed by two metrics, including the peak signal-to-noise ratio (PSNR) and the contrast-to-noise ratio (CNR). The results show the accuracy of the cortical segmentation was 96.07%. The PSNR and CNR values increased significantly in the projections of the selected cortical regions. The OCTA incorporating the deep learning-based cortical segmentation can efficiently improve the image quality and enhance the vasculature clarity.     

In vivo optoretinography of phototransduction activation and energy metabolism in retinal photoreceptors

The objective of this study is to verify the anatomic correlate of the second (2nd) outer retina band in optical coherence tomography (OCT), and to demonstrate the potential of using intrinsic optical signal (IOS) imaging for concurrent optoretinography (ORG) of phototransduction activation and energy metabolism in stimulus activated retinal photoreceptors. A custom-designed OCT was employed for depth-resolved IOS imaging in mouse retina activated by a visible light flicker stimulation. The spatiotemporal properties of the IOS changes at the photoreceptor outer segment (OS) and inner segment (IS) were quantitatively evaluated. Rapid IOS change was observed at the OS almost right away, and the IOS at the IS was relatively slow. Comparative analysis indicates that the OS-IOS reflects transient OS deformation caused by the phototransduction activation, and IS-IOS might reflect the energy metabolism caused by mitochondria activation in retinal photoreceptors. The consistency of the distribution of the IS-IOS and the 2nd OCT band supports the IS ellipsoid (ISe), which has abundant mitochondria, as the signal source of the 2nd OCT band of the outer retina.     

A feasibility study of OCT for anatomical and vascular phenotyping of mouse embryo

The embryo phenotyping of genetic murine model is invaluable when investigating functions of genes underlying embryonic development and birth defect. Although traditional imaging technologies such as ultrasound are very useful for evaluating phenotype of murine embryos, the use of advanced techniques for phenotyping is desirable to obtain more information from genetic research. This letter tests the feasibility of optical coherence tomography (OCT) as a high‐throughput phenotyping tool for murine embryos. Three‐dimensional OCT imaging is performed for live and cleared mouse embryos in the late developmental stage (embryonic day 17.5). By using a dynamic focusing method and OCT angiography (OCTA) approach, our OCT imaging of the embryo exhibits rapid and clean visualization of organ structures deeper than 5 mm and complex microvasculature of perfused blood vessels in the murine embryonic body. This demonstration suggests that OCT imaging can be useful for comprehensively assessing embryo anatomy and angiography of genetically engineered mice.     

En‐face optical coherence tomography for the detection of cancer in prostatectomy specimens: Quantitative analysis in 20 patients

The increase histopathological evaluation of prostatectomy specimens rises the workload on pathologists. Automated histopathology systems, preferably directly on unstained specimens, would accelerate the pathology workflow. In this study, we investigate the potential of quantitative analysis of optical coherence tomography (OCT) to separate benign from malignant prostate tissue automatically. Twenty fixated prostates were cut, from which 54 slices were scanned by OCT. Quantitative OCT metrics (attenuation coefficient, residue, goodness‐of‐fit) were compared for different tissue types, annotated on the histology slides. To avoid misclassification, the poor‐quality slides, and edges of annotations were excluded. Accurate registration of OCT data with histology was achieved in 31 slices. After removing outliers, 56% of the OCT data was compared with histopathology. The quantitative data could not separate malignant from benign tissue. Logistic regression resulted in malignant detection with a sensitivity of 0.80 and a specificity of 0.34. Quantitative OCT analysis should be improved before clinical use.     

Optical coherence tomography-based non-invasive evaluation of premalignant lesions in SKH-1 mice

Non-invasively diagnosis of actinic keratoses (AK) is important for preventing cutaneous squamous cell carcinoma (cSCC). Optical coherence tomography (OCT) can be used to detect the cross-sectional skin micromorphology with sufficient resolution and imaging depth. It has the capability to reveal the changes in skin microstructure during the development of AK. Therefore, OCT can serve as a tool for diagnosing AK. This study explores the feasibility of OCT in evaluating the structural changes in mouse skin at the different stages following exposure to ultraviolet radiation. The performance of OCT is compared with histology, the gold standard in this context. The imaging results demonstrate that a wave-shaped irregular dermo-epidermal junction (DEJ), as well as the continuous thickening of the epidermis, are useful diagnostic parameters for diagnosing AK. Histological examinations confirm these observations. These findings emphasize the need for effective skin protection or medical treatment once changes in the DEJ and epidermis are detected. OCT shows strong potential for non-invasive evaluation of such changes and AK development, and can be used for the prevention of cSCC without the necessity of taking biopsies.     

A spatial resolution evaluation method of endoscopic optical coherence tomography system using the annular phantom

As an important biomedical imaging method, endoscopic optical coherence tomography (OCT) is necessary to check its performance regularly. The ordinary plane phantoms are only able to evaluate part of image tangent to the probe. In this research, a spatial resolution estimate method of the endoscope OCT system is proposed. The annular phantom, made by uniformly distributing golden scattered microparticles in polydimethylsiloxane (PDMS), can provide dynamic scanning imaging evaluation of endoscopic OCT system, closer to its actual working status. The point spread function analysis method is used to analyze the imaging results of the annular phantom with the endoscopic OCT system. And many scattered particles are statistically analyzed to determine the spatial resolution of the endoscope OCT system. The method is low in cost, simple and convenient. It is valuable for the development of test standards for endoscope OCT systems.     

A novel automatic 3D stitching algorithm for optical coherence tomography angiography and its application in dermatology

Optical coherence tomography (OCT) and OCT angiography (OCTA) techniques offer numerous advantages in clinical skin applications but the field of view (FOV) of current commercial systems are relatively limited to cover the entire skin lesion. The typical method to expand the FOV is to apply wide field objective lens. However, lateral resolution is often sacrificed when scanning with these lenses. To overcome this drawback, we developed an automated 3D stitching method for creating high-resolution skin structure and vascular volumes with large field of view, which was realized by montaging multiple adjacent OCT and OCTA volumes. The proposed stitching method is demonstrated by montaging 3 × 3 OCT and OCTA volumes (nine OCT/OCTA volumes as one data set with each volume covers 2.5 cm × 2.5 cm area) of healthy thin and thick skin from six volunteers. The proposed stitching protocol achieves high flexibility and repeatable for all the participants. Moreover, according to evaluation of structural similarity index and feature similarity index, our proposed stitched result has a superior similarity to single scanning protocol in large-scaled. We had also verified its improved performance through assessing metrics of vessel contrast-noise-ratio (CNR) from 2.07 ± 0.44 (single large-scaled scanning protocol) to 3.05 ± 0.51 (proposed 3 × 3 sub-volume stitching method).     

Jones matrix‐based speckle‐decorrelation angiography using polarization‐sensitive optical coherence tomography

We show that polarization‐sensitive optical coherence tomography angiography (PS‐OCTA) based on full Jones matrix assessment of speckle decorrelation offers improved contrast and depth of vessel imaging over conventional OCTA. We determine how best to combine the individual Jones matrix elements and compare the resulting image quality to that of a conventional OCT scanner by co‐locating and imaging the same skin locations with closely matched scanning setups. Vessel projection images from finger and forearm skin demonstrate the benefits of Jones matrix‐based PS‐OCTA. Our study provides a promising starting point and a useful reference for future pre‐clinical and clinical applications of Jones matrix‐based PS‐OCTA.     

Vascular changes precede tomographic changes in diabetic eyes without retinopathy and improve artificial intelligence diagnostics

The purpose of this study was to evaluate early vascular and tomographic changes in the retina of diabetic patients using artificial intelligence (AI). The study included 74 age‐matched normal eyes, 171 diabetic eyes without retinopathy (DWR) eyes and 69 mild non‐proliferative diabetic retinopathy (NPDR) eyes. All patients underwent optical coherence tomography angiography (OCTA) imaging. Tomographic features (thickness and volume) were derived from the OCTA B‐scans. These features were used in AI models. Both OCT and OCTA features showed significant differences between the groups (P < .05). However, the OCTA features indicated early retinal changes in DWR eyes better than OCT (P < .05). In the AI model using both OCT and OCTA features simultaneously, the best area under the curve of 0.91 ± 0.02 was obtained (P < .05). Thus, the combined use of AI, OCT and OCTA significantly improved the early diagnosis of diabetic changes in the retina.     

Determination and correction of aberrations in full field optical coherence tomography using phase gradient autofocus by maximizing the likelihood function

A method for numerical estimation and correction of aberrations of the eye in fundus imaging with optical coherence tomography (OCT) is presented. Aberrations are determined statistically by using the estimate based on likelihood function maximization. The method can be considered as an extension of the phase gradient autofocusing algorithm in synthetic aperture radar imaging to 2D optical aberration correction. The efficacy of the proposed method has been demonstrated in OCT fundus imaging with 6λ aberrations. After correction, single photoreceptors were resolved. It is also shown that wave front distortions with high spatial frequencies can be determined and corrected.     

Long‐term and in vivo assessment of Aβ protein‐induced brain atrophy in a zebrafish model by optical coherence tomography

In this study, a neurotoxicity model of zebrafish induced by amyloid beta (Aβ) protein was developed and evaluated in vivo by optical coherence tomography (OCT). Aβ protein and phosphate buffer saline (PBS) were separately injected into the head of two groups of adult zebrafish (n = 6 per group). Congo‐red staining results confirmed that Aβ protein had penetrated into brain tissue. All zebrafish were imaged with OCT on the 0th, 5th, 10th, 15th and 20th day postinjection. OCT images showed that PBS is not toxic to brain tissue. However, significant brain atrophy could be seen in the OCT images of zebrafish injected with Aβ‐protein that was verified by histological consequences. In addition, zebrafish in the model group showed memory decline in behavioral tests. This study verified the feasibility of in vivo long‐term assessment of Aβ protein‐induced brain atrophy in adult zebrafish by OCT that has great potential to be applied in the neurological diseases research.