Optical coherence tomography angiography (OCTA) takes the flowing red blood cells (RBCs) as intrinsic contrast agents, enabling fast and three-dimensional visualization of vasculature perfusion down to capillary level, without a requirement of exogenous fluorescent injection. Various motion-contrast OCTA algorithms have been proposed to effectively extract dynamic blood flow from static tissues utilizing the different components of OCT signals (including amplitude, phase and complex) with various operations (such as differential, variance and decorrelation). Those algorithms promote the application of OCTA in both clinical diagnosis and scientific research. The purpose of this paper is to provide a systematical review of OCTA based on the inverse SNR and decorrelation features (ID-OCTA), mainly including the OCTA contrast origins, ID-OCTA imaging, quantification and applications.

Surgical excision is an effective treatment for oral squamous cell carcinoma (OSCC), but exact intraoperative differentiation OSCC from the normal tissue is the first premise. As a noninvasive imaging technique, optical coherence tomography (OCT) has the nearly same resolution as the histopathological examination, whose images contain rich information to assist surgeons to make clinical decisions. We extracted kinds of texture features from OCT images obtained by a homemade swept-source OCT system in this paper, and studied the identification of OSCC based on different combinations of texture features and machine learning classifiers. It was demonstrated that different combinations had different accuracies, among which the combination of texture features, gray level co-occurrence matrix (GLCM), Laws' texture measures (LM), and center symmetric auto-correlation (CSAC), and SVM as the classifier, had the optimal comprehensive identification effect, whose accuracy was 94.1%. It was proven that it is feasible to distinguish OSCC based on texture features in OCT images, and it has great potential in helping surgeons make rapid and accurate decisions in oral clinical practice.

Accurate segmentation of choroidal thickness (CT) and vasculature is important to better analyze and understand the choroid-related ocular diseases. In this paper, we proposed and implemented a novel and practical method based on the deep learning algorithms, residual U-Net, to segment and quantify the CT and vasculature automatically. With limited training data and validation data, the residual U-Net was capable of identifying the choroidal boundaries as precise as the manual segmentation compared with an experienced operator. Then, the trained deep learning algorithms was applied to 217 images and six choroidal relevant parameters were extracted, we found high intraclass correlation coefficients (ICC) of more than 0.964 between manual and automatic segmentation methods. The automatic method also achieved great reproducibility with ICC greater than 0.913, indicating good consistency of the automatic segmentation method. Our results suggested the deep learning algorithms can accurately and efficiently segment choroid boundaries, which will be helpful to quantify the CT and vasculature.

In this work, we report a method of removing scattering induced retardance in polarization sensitive full field optical coherence tomography (PS-FFOCT). First, the Mueller matrix that describes its operation is derived. The thickness invariant retardance induced by the scattering of collagenous fiber bundles is then used to find the accurate values of the birefringence of the layers that consist collagenous fibers. Finally, the initial en face birefringent images of in vitro beef tendon samples are presented to demonstrate the capability of our method.

Purpose: To introduce the application of intraoperative optical coherence tomography (iOCT) in pars plana vitrectomy (PPV) for various vitreoretinal diseases, and to report the 4-year assessment of feasibility and utility in Chinese population. Methods: Retrospective case series of patients who underwent PPV and iOCT scan at Eye Hospital of Wenzhou Medical College from January 2016 to January 2020. Clinical characteristics were documented before operation, and we intraoperatively recorded the time and results of iOCT scanning, specific surgical maneuvers performed, the consistency with the planned strategies before surgery, the type of OCT images obtained, and adverse events (AEs). The surgeon feedback was collected to evaluate the utility of iOCT during surgery. Results: In total 339 eyes successfully completed iOCT scan, with an average scanning time of 3.54 ± 2.3 min, including 59 cases of idiopathic macular hole (iMH), 134 cases of idiopathic epiretinal membrane (iERM), 33 cases of lamellar macular hole (LMH), 40 cases of high myopic maculopathy, 13 cases of vitreous macular traction (VMT), 60 cases of dense vitreous hemorrhage (VH). The iOCT findings were not consistent with examination under the operating microscope in 49 cases (14.5%), including 29 cases (8.6%) which changed the operation strategies during surgery. The Hole-door phenomenon arose in 20 cases (33.9%) of iMH and 3 cases (25%) of high myopic MH after ILMs peeling. Moreover, the residue ERM was observed in nine cases (6.7%) of iERM and two cases (14.3%) in high myopic ERM after ILMs peeling. Some new surgical methods could also be confirmed using iOCT. Conclusion: The application of iOCT has a significant clinical functionality in vitreoretinal surgery, providing the surgeon with a new surgical understanding, guiding the selection of a more reasonable operative procedure during surgery, predicting postoperative recovery and improving postoperative outcomes.

In this study, we proposed a method to measure the epidermal thickness (ET) of skin based on deep convolutional neural network, which was used to determine the boundaries of skin surface and the ridge portion in dermal–epidermis junction (DEJ) in cross-section optical coherence tomography (OCT) images of fingertip skin. The ET was calculated based on the row difference between the surface and the ridge top, which is determined by search the local maxima of boundary of the ridge portion. The results demonstrated that the region of ridge portion in DEJ was well determined and the ET measurement in this work can reduce the effect of the papillae valley in DEJ by 9.85%. It can be used for quantitative characterization of skin to differentiate the skin diseases.

Cerebral edema is a severe complication of acute ischemic stroke with high mortality but limited treatment. Although parameters such as brain water content and intracranial pressure may represent the global assessment of edema, optical properties can appear heterogeneously throughout the cerebral tissue relative to the site of injury. In this study, we have monitored the edema formation and progression in both permanent and transient middle cerebral artery occlusion models in rats. Edema was reflected by the decrease of optical attenuation coefficient (OAC) value in OCT system. By utilizing swept-source optical coherence tomography (SS-OCT), we found that in photochemically induced permanent focal stroke model, both the edema size and edema index, steadily developed until the end of monitor (7 h). Comparatively, when transient ischemia was introduced with endothelin-1 (ET-1), the edema was detected as early as 15 min, and began to recover after 30 min until monitor was finished (3 h). Despite the majority of the edema being recovered to some extent, the condition of a small region within the edema kept deteriorating, presumably due to the reperfusion damage which might result in serious clinical outcomes. Our study has compared the edema characteristics from two different acute ischemic stroke situations. This work not only confirms the capability of OCT to temporal and spatial monitor of edema but is also able to locate focal conditions at some areas that might highly determine the prognosis and treatment decisions.

As a high-resolution optical imaging technology, Optical Coherence Tomography (OCT) has been widely used in the diagnosis and treatment of cardiovascular diseases. It has played an important role in the detection and identification of atherosclerotic plaques and has significant advantages. In this paper, we realized to extract the optical characteristic parameters of the target sample based on the OCT data by establishing optical transmission models conforming to the OCT principle. The optical phantoms and coronary artery of domestic pig were used as research samples to study the difference between the optical properties of the cardiovascular tissues. It can provide a basic method for further study of optical characteristic parameters of atherosclerotic plaques, and also lay a foundation for realizing the quantitative evaluation of atherosclerotic plaques with multiple optical characteristic parameters in the future.

We propose a k-domain spline interpolation method with constrained polynomial fit based on spectral phase in swept-source optical coherence tomography (SS-OCT). A Mach–Zehnder interferometer (MZI) unit is connected to the swept-source of the SS-OCT system to generate calibration signal in sync with the fetching of interference spectra. The spectral phase of the calibration signal is extracted by Hilbert transformation. The fitted phase–time relationship is obtained by polynomial fitting with the constraint of passing through the central spectral phase. The fitting curve is then adopted for k-domain uniform interpolation based on evenly spaced phase. In comparison with conventional k-domain spline interpolation, the proposed method leads to improved axial resolution and peak response of the axial point spread function (PSF) of the SS-OCT system. Enhanced performance resulting from the proposed method is further verified by OCT imaging of a home-constructed microspheres-agar sample and a fresh lemon. Besides SS-OCT, the proposed method is believed to be applicable to spectral domain OCT as well.

To accurately guide surgical instruments during ophthalmic procedures, some necessary intraoperative depth perception is required, which standard surgical microscopes supply limitedly. Intraoperative optical coherence tomography (iOCT), combining optical coherence tomography (OCT) technology and surgical microscope, enables noninvasive, real-time and highresolution cross-sectional imaging. Currently, though iOCT enables structural imaging, little research has been done on intraoperative angiography. In this work, we presented a swept-source intraoperative OCT angiography (SS-iOCTA) system based on a standard surgical microscope, which provides both structural and angiographic images. The feasibility of the proposed SSiOCTA was confirmed through deep anterior lamellar keratoplasty (DALK) of ex vivo porcine eyes and blood perfusion imaging of in vivo rat cortex. High-resolution intraoperative feedback, including sub-surface structure and angiogram of biological tissue, can be visualized simultaneously with the SS-iOCTA system, which expand the surgeon's capabilities and could be widely used in clinical surgery.

It is necessary to investigate the wavelength-dependent variation rules of the refractive index of edible oils so as to explore the specificity of the dispersion in light propagation, imaging, and interference processes among different types of edible oil products. In this study, by deriving the refractive index equations of the double glass sheet holding device and oil, the reflectance spectra of three different types of oil samples, namely, peanut oil, colza oil, and kitchen waste oil, were measured via a spectrometer. Furthermore, the refractive index model of these different types of oil samples was investigated. Additionally, based on the oil dispersion characteristics, the dispersion of oil in optical coherence tomography (OCT) was compensated via deconvolution. In the wavelength range of λ∈ (380, 1500) nm, the analytical expressions of the double glass sheet holding device and oils are featured by practical reliability. The refractive indexes of three different types of oils n ∈ (1.38, 1.52) show normal dispersion characteristics. The Cauchy coeffi cient matrix of the oil refractive index can be used for oil identification; in particular, the healthy oil and waste oil differ significantly in terms of the Cauchy coefficient matrix in the infrared band. Oil dispersion has almost no influence on the phase spectra of oils but can enhance their amplitude spectra. The dispersion mismatch can be eliminated by calculating the convolution kernel. The envelope broadening factors of OCT interference signals of oil products are 0.84, 0.64, and 0.91, respectively. According to the present research results, the refractive index model of oil can effectively remove the influence of the holding device. The refractive indexes of three different types of oil samples show similar wavelength-dependent variation characteristics, which confirms the existence of many correlated components in these oil samples. The established refractive index model of oil in a wide spectral range, from the ultraviolet to the infrared band, can be adequately employed for identifying different types of oils. The numerical dispersion compensation based on the established refractive index model can enhance the axial resolution in OCT imaging.

Segmentation of layers in retinal images obtained by optical coherence tomography (OCT) has become an important clinical tool to diagnose ophthalmic diseases. However, due to the susceptibility to speckle noise and shadow of blood vessels etc., the layer segmentation technology based on a single image still fail to reach a satisfactory level. We propose a combination method of structure interpolation and lateral mean filtering (SI-LMF) to improve the signal-to-noise ratio based on one retinal image. Before performing one-dimensional lateral mean filtering to remove noise, structure interpolation was operated to eliminate thickness fluctuations. Then, we used boundary growth method to identify boundaries. Compared with existing segmentations, the method proposed in this paper requires less data and avoids the influence of microsaccade. The automatic segmentation method was verified on the spectral domain OCT volume images obtained from four normal objects, which successfully identified the boundaries of 10 physiological layers, consistent with the results based on the manual determination.