Quantum-mimetic (QM) optical coherence tomography (OCT) combined with wavefront shaping is proposed as a novel approach to achieve high-resolution cross-sectional imaging through a strongly scattering medium. Specifcally, QM-OCT is a recently devised OCT technique mimicking quantum OCT to acquire its main characteristic features, most notably immunity to group-velocity dispersion and enhancement of axial resolution, without quantum light. To validate the proposed method, we demonstrate experimentally that a one-dimensional cross-sectional image of a sample located behind a diffuser plate is obtained successfully and efficiently with QM-OCT by shaping the wavefront of light incident onto the diffuser.

Chronic rhinitis (CR) is among the most frequent inflammatory diseases of ear-nose-throat (ENT) covering up to 30% of the population. Different forms of CR require different treatment tactics, which indicates the need for an efficient tool for differential diagnostics of CR. Optical coherence tomography (OCT) is a promising tool for fast non-invasive evaluation of nasal mucosa, which, however, requires further interpretation of the obtained diagnostic image. In this paper, we provide a comparative analysis of several machine learning approaches that aim at automated differential diagnostics of CR based on diagnostic OCT images of 78 patients aged between 28 and 74 ...

To preserve the fertility of young female cancer patients, ovarian tissue cryopreservation and transplantation have been investigated as next-generation reproductive medical technologies. Non-invasive visualization of follicles in ovarian tissue and cryopreservation of higher density tissue is essential for effective transplantation. We proposed the use of optical coherence tomography (OCT) that can noninvasively visualize the internal structure of the ovarian tissue. However, a method for quantifying cell density has not yet been established because of the lack of available techniques to visualize follicles noninvasively. We proposed the use of a convolutional neural network (CNN) to extract small features from medical images ...

Currently, breast tissue images are primarily classified by pathologists, which is time-consuming and subjective. Deep learning, however, can perform this task with the utmost precision. In order to achieve an improved performance, a large number of annotated datasets are required to train the network, which is a challenging task in the medical field. In this paper, we propose an intelligent system, based on generative adversarial networks (GANs) and a convolution neural network (CNN) for the automatic classification of breast cancer, using optical coherence tomography (OCT) images. In this network, the GAN is used to generate synthetic datasets and to further ...

The method for displacement correction along the slow axis of optical coherence tomography (OCT) data volumes is presented. The method is based on the recursive replacement of the next displaced OCT measurements by the weighted summation of itself and the previous OCT measurement in the slow axis dimension already corrected for the displacement. The values of the appropriate weight multipliers were defined from the local correlation of the two measurements. The proposed method was used as a preprocessing step for optical coherence angiography processing of the OCT data. A substantial reduction of the motion-induced stripe artifact was demonstrated.

An endoscopic optical coherence tomography (OCT) probe that can perform full circumferential scans using a circular array of six micro-electro-mechanical system (MEMS) mirrors has been developed. Inside the OCT probe, each of the six MEMS mirrors forms an independent scanning unit; circumferential OCT images are acquired by off-centre scanning and combining the image data from the individual multiple scanning units. Here, an imaging analysis and reconstruction (IAR) method is proposed to construct endoscopic OCT volumetric images from the multiple individual MEMS scanning unit. Imaging procedures of six-MEMS mirrors-based, eight-MEMS mirrors-based and twelve-MEMS mirrors-based OCT probes have been analyzed theoretically. All ...

In this paper, an angular compounding method to achieve speckle contrast reduction in optical coherence tomography (OCT) imaging is explored in detail. The angular compounding approach involves collecting multiple images at different angles of incidence, registering the images to correct for induced distortions, and then incoherently summing the images to reduce speckle. The method was experimentally demonstrated with a spectrometer-based Master–Slave enhanced OCT instrument capable of directly generating en-face images. We have investigated the impact of the angular range and number of averaged frames on the degree of speckle artefact reduction, as well as the effect on image resolution ...

In conventional SD-OCT, a beam is focused to one spot on the surface of the sample to acquire depth information beneath that spot. Adjacent spots are serially scanned to obtain a tomographic image of the sample; thus, available OCT techniques can take significant time to scan large objects. This paper illustrates an SD-OCT system involving spectral-slicing of a broadband spectrum to enable the simultaneous acquisition from multiple lateral positions of the sample. Using a wavelength encoding of spatial information, where each lateral location is associated with a specific portion of a source spectrum, multiple lateral spots are interrogated concurrently to ...

In this paper, an angular compounding method to achieve speckle contrast reduction in optical coherence tomography (OCT) imaging is explored in detail. The angular compounding approach involves collecting multiple images at different angles of incidence, registering the images to correct for induced distortions, and then incoherently summing the images to reduce speckle. The method was experimentally demonstrated with a spectrometer-based Master-Slave enhanced OCT instrument capable of directly generating en-face images. We have investigated the impact of the angular range and number of averaged frames on the degree of speckle artefact reduction, as well as the effect on image resolution and ...

Intravascular optical coherence tomography (IVOCT) is becoming an important choice for in vivo diagnosis of coronary artery diseases. The atherosclerotic disease can be detected from IVOCT images, but the segmentation of IVOCT images and identification of plaques are mainly performed manually. This process is laborious and time consuming and its accuracy relies on the expertise of the observer. To address these limitations, a semi-automated identification algorithm based on texture features is presented in this paper. Regions of interest (ROIs) in IVOCT images are firstly selected, then texture features are calculated to represent this ROI. Finally, an artificial neural network is ...

Cross polarized optical coherence tomography offers enhanced contrast in certain pathological conditions. Traditional cross-polarized optical coherence tomography systems require a defined input polarization and thus require several polarization controlling elements increasing the overall complexity of the system. Our proposed system requires a single quarter wave plate as a polarization controller thus simplifying the system significantly. Majority of Cross-polarized optical coherence tomography systems are spectrometer based which suffers from slow speed and low signal to noise ratio. In this work, we present a swept source based cross-polarized optical coherence tomography system that works for any input polarization state. The system was ...

This paper reports the development of a new technique, free space line field spectral domain optical coherence reflectometry (LF-SD-OCR), which is able to produce tomographic like (quasi) images. Furthermore, the capabilities and cost benefits of the technique are demonstrated by constructing a handheld LF-SD-OCR device. For glossy paint systems and other suitable samples, the line field format produces quasi-tomographic (cross-sectional) imaging through the layers, with axial and lateral image resolutions of 1.3 µm and 40 µm respectively. From these, the clear coat thicknesses on the bonnet of cars were measured by graph search segmentation and maximum A-scan projection. In ...

This study explores the development of high-speed swept source with a wide imaging range and instantaneous line width. For the swept source in the 1.3-μm band, the sweep rate is 193.25 kHz through the sampling buffer structure, the maximum tuning range is 142.34 nm. Meanwhile, the numerical model of the SS–OCT system is established and the signal in the OCT imaging process is numerically simulated. The influence of the dispersion mismatch point diffusion function on the imaging system is studied. Simulation results provide valuable guidance for the selection of optical components in the SS–OCT ...

The method for visualization of the low-scattering objects inside the bulk of the high-scattering tissue is presented. The method can contrast the low-scattering object of interest not only from the high scattering surroundings but from the noise region below the tissue image as well. The proposed method was applied for the visualization of the rodent and human cochlea volume.

With the demand for high-resolution images, the storage space occupied by the images of the full-field optical coherence tomography (FFOCT) system is becoming more and more intensified. How to reduce the data volume of high-resolution image systems has become a research hotspot in the image processing industry. In particular, precision medicine requires high-resolution images of organs and tissues, and this data storage system requires a large storage space. For this reason, based on the high-resolution tomographic image obtained from our organ tissue, compressed sensing theory is used to perform compression reconstruction simulation. It is verified that the amount of data ...

The degree of coherence of radiation is an important characteristic on which the interference properties of light fields and, as a consequence, the resolution of optical systems depend. When propagating over long distances even in free space, initially completely coherent or incoherent radiation becomes partially coherent. This fact should be taken into account in the formation of optical images along with the influence of wave front aberrations. In this paper, we investigate the change in the resolution of the system for two near-point light sources depending on the degree of spatial coherence in the presence of different aberrations. The possibility ...

Endoscopic optical coherence tomography is an interference based imaging technique which due to its micron level resolution ability found several applications in medical diagnostics. However, the standard image performance suffers from artefacts caused by dispersion imbalance and polarisation mismatches between reference and sample arm. Such artefacts can be minimised with the use of a special class of probes called common path probes where the reference surface is placed in the vicinity of the sample. Previously reported common path probes suffered from a compromise between sensitivity and resolution. In most cases, proposed probes were not scalable for industrial applications and required ...

We present a novel design of all-normal flat near zero dispersion chalcogenide photonics crystal fiber (PCF) for mid-infrared supercontinuum (SC) generation. The proposed PCF with a core made of As₂Se₃ glass and uniform air holes in the cladding is selectively filled with As₂S₅ glass. By carefully engineering the PCF with an all-normal flat near zero dispersion profile, the anomalous-dispersion soliton effects are reduced, enabling broadband highly coherent SC generation. We also investigate the impacts of the pulse parameters on the SC generation. Broadband SCs covering 1 ...

As is generally known, broad-band near-infrared Supercontinuum (SC) is significant for the applications such as pump-probe spectroscopy, nonlinear spectroscopy, frequency combs, or nonlinear optical parametric amplification. We present the first detailed demonstration of approximate near-infrared, octave-spanning SC generation in all-normal dispersion CS2 single-hole liquid core optical fiber (LCOF). By solving the generalized nonlinear Schrödinger equation, the SC at different parameters can be calculated. The influence of important parameters including but not limited to fiber core-diameter, pump wavelength, pump power, and pulse width, on the supercontinuum generation (SCG) of CS2 infiltrated LCOF can be analyzed for optimization of near-infrared SC ...

Optical coherence tomography is radiation-free, and it is considered a tool of optical biopsy. Classification of normal and cancerous tissues is very important for the guidance of surgeons. Here, we develop the morphological feature analysis-based classification (MFAC) method, combining it with machine learning to identify cancerous tissues. We extract five quantitative morphological features from one OCT image through the structured analysis. Five classifiers are involved to make a classification: the support vector machine, the K -nearest neighbor, the random forest, logic regression, and the conventional threshold method. Sensitivity, specificity, and accuracy are used to evaluate these classifiers and are compared ...

Abstract: We propose a simple method of linearizing spectral interference fringes of spectral domain optical coherence tomography (SD-OCT) based on B-scan Doppler frequency shift (DFS), which can be obtained by offsetting the laser beam from the pivot of a scanning mirror. We show that DFS is proportional to wavenumber. A DFS based calibration curve can be then extracted from either a single mirror image or multiple tissue images. By examining the convergence of the nonlinear coefficients of the DFS curve fitted with a polynomial equation, tissue images themselves can be used to linearize the wavenumber without requiring mirror images or ...

Speckle is a major quality degrading factor in optical coherence tomography (OCT) images. In this work we propose a new deep learning network for speckle reduction in retinal OCT images, termed DeSpecNet. Unlike traditional algorithms, the model can learn from training data instead of manually selecting parameters such as noise level. The proposed deep convolutional neural network (CNN) applies strategies including residual learning, shortcut connection, batch normalization and leaky rectified linear units to achieve good despeckling performance. Application of the proposed method to the OCT images shows great improvement in both visual quality and quantitative indices. The proposed method provides ...

A quantitative spectrometer-based photothermal optical coherence tomography (PT-OCT) system is employed to investigate and image the photothermal trapping of gold nano-rods (GNRs) in clear and biological media. The PT-OCT system is calibrated through dynamic phase measurements of piezo motion with known driving parameters. We measure and compare the displacement sensitivities of the PT-OCT system at different camera exposure time settings in two configurations: with a distinct reference path; and with a common path. The displacement sensitivity of the system in the common path configuration is improved from 1.5 nm to 0.17 nm by performing Fourier analysis on the ...

A full-wave model for simulating images in spectral-domain optical coherence tomography (OCT) with rigorous accounting for the beam-focusing effects is developed. Due to the analytical description of beam focusing, the model is computationally rather efficient. It also uses a rigorous numerical summation of the contributions of the localized sub-resolution scatterers, accounting for variations in the phase-amplitude parameters of the incident and backscattered optical waves, with a subsequent integration of the latter over the objective aperture. In the limit of a weakly focused beam, the developed model has allowed for the validatation of the earlier proposed simplified model with a constant-radius ...