Fourier-domain full-field optical coherence tomography (FD-FF-OCT) has the advantages of high resolution and parallel detection. However, using parallel detection can result in optical crosstalk. Toward minimizing crosstalk, we implemented a very fast deformable membrane (DM) that introduces random phase illumination, which can effectively reduce the crosstalk by washing out fringes originating from multiply scattered light. However, for one thing, although the application of DM has reduced the crosstalk problem in parallel detection to a certain extent, there will still be a lot of background noises, which may come from the circadian rhythm of the sample and multiple scattered photons. The ...

This book covers the state-of-the-art techniques of optical coherence tomography angiography (OCTA) imaging for the diagnosis of retinal diseases. It is part of a three-volume work that describes the latest imaging techniques in which to bring optical coherence tomography (OCT), Fundus Imaging and optical coherence tomography angiography (OCTA) to accurately facilitate the diagnosis of retinal diseases. Clinical disorders of the retina have been attracting the attention of researchers, aiming at reducing the blindness rate. This includes uveitis, diabetic retinopathy, macular edema, endophthalmitis, proliferative retinopathy, age-related macular degeneration and glaucoma. Treatment is significantly dependent on having early and accurate diagnosis, which ...

Percutaneous Coronary Intervention (PCI) with stent placement is a treatment effective for coronary artery diseases. Intravascular optical coherence tomography (OCT) with high resolution is used clinically to visualize stent deployment and restenosis, facilitating PCI operation and for complication inspection. Automated stent struts segmentation in OCT images is necessary as each pullback of OCT images could contain thousands of stent struts. In this paper, a deep learning framework is proposed and demonstrated for the automated segmentation of two major clinical stent types: metal stents and bioresorbable vascular scaffolds (BVS). U-Net, the current most prominent deep learning network in biomedical segmentation, was ...

Choroid thickness measured from optical coherence tomography (OCT) images has emerged as a vital metric in the management of retinal diseases such as high myopia. In this paper, we propose a novel group-wise context selection network (referred to as GCS-Net) to segment the choroid of either normal or high myopia eyes. To deal with the diverse choroid thickness and the variable shape of the pathological retina, GCS-Net adopts the group-wise channel dilation (GCD) module and the group-wise spatial dilation (GSD) module, which can automatically select group-wise multi-scale information under the guidance of channel attention or spatial attention, and enhance the ...

Optical coherence tomography (OCT) is a well-established imaging technology for high-resolution, cross-sectional imaging of biological tissues. Imaging processing and light attenuation coefficient estimation allows to further improve the OCT diagnostic capability. In this paper we use a commercial OCT system, Telesto II-1325LR from Thorlabs, and demonstrate its ability to differentiate normal and tumor mammary mouse glands with the OCT attenuation coefficient. Using several OCT images of normal and tumor mammary mouse glands (n=26), a statistical analysis was performed. The attenuation coefficient was calculated in depth, considering a slope of 0.5 mm. The normal glands present a median attenuation ...

Background and objective Optical Coherence Tomography (OCT) is one of the most used retinal imaging modalities in the clinic as it can provide high-resolution anatomical images. The huge number of OCT images has significantly advanced the development of deep learning methods for automatic lesion detection to ease the doctor's workload. However, it has been frequently revealed that the deep neural network (DNN) model has difficulty handling the domain discrepancies, which widely exist in medical images captured from different devices. Many works have been proposed to solve the domain shift issue in deep learning tasks such as disease classification and ...

Optical coherence tomography (OCT) is a non-invasive imaging te chnique, which has high resolution and high sensitivity. Due to its real-time, cross-sectional, an d micrometer-scale imaging capabilities, OCT has been widely used in ophthalmology [1]. In ophthalmic im aging, OCT allowed for not only the analysis of anterior segment structures like cornea and iri s, but also the visualization of details like trabecular meshwork and Schlemm’s canal. Clinically, real-time OCT images help surgeons to evaluate the lesion and plan surgical paths. With the developme nt of swept-source optical coherence tomography (SS-OCT), the axial scanning speed has reached multi -MHz ...

Optical Coherence Tomography (OCT) is a promising non-invasive imaging technique that owns many biomedical applications. In this paper, a deep neural network is proposed for enhancing the spatial resolution of OCT en face images. Different from the previous reports, the proposed can recover high resolution en face images from low resolution en face images at arbitrary imaging depth. This kind of imaging depth adaptive resolution enhancement is achieved through an external attention mechanism, which takes advantage of morphological similarity between the arbitrary-depth and full-depth en face images. Firstly, the deep feature maps are extracted by a feature extraction network from ...

A method combining phase-contrast technique and spectral-domain optical coherence tomography (OCT) has been recently proposed for visualizing curing behaviors inside polymers (2020 Appl. Phys. Lett. 116 054103). Here, based on the method, a non-contact and highly-sensitive optical sensor is further developed to monitor the photocuring process of light-cured polymers. Compared with the existing method, the proposed optical sensor features two distinct advantages: (a) the sensor uses a point-detection OCT, rather than a line-field OCT, to capture the interference signal, which significantly improves its practicability and the measuring speed; (b) the sensor can simultaneously monitor the shrinkage strains and refractive index ...

This study aimed to demonstrate the feasibility of using optical coherence tomography (OCT) for locating the sectioning site of a specimen before characterizing the ultrastructural features of dentin surfaces as well as the inner wall of the dentinal tubules (DT) using a field emission scanning electron microscope (FESEM). Eight sound human molar teeth were extracted, examined via cross-polarization optical coherence tomography (CP-OCT), embedded, and hemisectioned using a low-speed diamond sawing machine. Next, each sectioned surface was further trimmed, polished, and examined under a confocal laser scanning microscope (CLSM) to locate the target area on the superficial dentin. Subsequently, each section ...

This study aims to monitor and assess the penetration and accumulation of gold nanoparticles (Au NPs) or silver nanoparticles (Ag NPs) (average particle size 40 nm) and the penetration of the Au NPs or Ag NPs assisted by electrical impulses (EP) in human normal femoral head (NFH) and pathological femoral head (PFH) tissues. The results show that optical coherence tomography images can easily distinguish NFH from PFH tissues. The control group show that the average attenuation coefficient of NFH tissue is 4.895 mm −1 , and the average attenuation coefficient of PFH tissue is 8.094 mm −1 . It shows ...

Soil acidification has shown detrimental effects on rice plants that lead to decreased rice production. In the present study, we aim to study the microstructural changes in rice leaves under acidic stress through swept-source optical coherence tomography (SS-OCT). To achieve this, rice seeds were germinated, subsequently these germinated seedlings were further grown under varying pH conditions for 14 d. Growth in root and shoot of plants and chlorophyll content of leaf samples were studied at varying pH levels. Similarly, acidic stress treated rice leaves were also subjected to SS-OCT image analysis revealing several features present in the layers of leaves ...

Optical coherence tomography (OCT) is a powerful optical imaging technique capable of visualizing the internal structure of biological tissues at near cellular resolution. For years, OCT has been regarded as the standard of care in ophthalmology, acting as an invaluable tool for the assessment of retinal pathology. However, the costly nature of most current commercial OCT systems has limited its general accessibility, especially in low-resource environments. It is therefore timely to review the development of low-cost OCT systems as a route for applying this technology to population-scale disease screening. Low-cost, portable and easy to use OCT systems will be essential ...

Within the last decades, several studies have been published that prove the benefit of polarisation sensitive optical coherence (psOCT) tomography for the field of biomedical diagnostics. However, polarisation sensitive imaging typically requires careful control of the polarisation state of the input illumination, which leads to bulky and delicate systems. While psOCT provides quantitative information, it is mostly sufficient to analyse the images qualitatively in the field of biomedical diagnostics. Therefore, a reduced form of this technique, cross-polarised optical coherence tomography (cpOCT), moves into the focus of interest that serves to visualise the birefringence properties of a sample. Despite the low ...

In this work, we reported on the implementation of compressive sensing (CS) and sparse sampling in polarization - sensitive optical coherence tomography (PS-OCT) to reduce the number of B-scans (frames consisting of an array of A-scans, where each represents a single depth profile of reflections) required for effective volumetric (3D dataset composed of an array of B-scans) PS-OCT mea surements (i.e., OCT intensity, and phase retardation) reconstruction. Sparse sampling of PS-OCT is achieved through randomization of step sizes along slow-axis of PS-OCT imaging, covering the same spatial ranges as those with equal slow-axis step sizes, but with a reduced number ...

Developing a high-resolution non-invasive optical coherence tomography angiography (OCTA) method for iris vasculature imaging is essential for diagnosing a wide range of ocular pathologies. However, the current iris-OCTA devices are still limited in imaging quality and penetration depth for dark-colored eyes ranging from brown to dark brown. A spectral domain iris-OCTA system is presented in this paper incorporating a 1300 nm wavelength for deeper tissue penetration, a linear-wavenumber spectrometer for better detection sensitivity, and an iris scan objective lens for better optical focusing across the entire iris over a 12 × 12 mm2 scan field. The −6 dB fall-off range is ...

Despite chemotherapy, residual tumors often rely on so-called drug tolerant persister (DTP) cells, which evade treatment to give rise to therapy-resistant relapse and refractory disease. Detection of residual tumor cells proves to be challenging because of the rarity and heterogeneity of DTP cells. In the framework of a H2020 project, REAP will gather researchers and engineers from six countries, who will combine their expertise in biology, chemistry, oncology, material sciences, photonics, and electrical and biomedical engineering in the hope of revealing DTPs in cancer using contrast enhanced multimodal optical imaging. Laser sources for photoacoustic microscopy (PAM), photoacoustic tomography (PAT), and ...

Microfabricated neuroprosthetic devices have made possible important observations on neuron activity; however, long-term high-fidelity recording performance of these devices has yet to be realized. Tissue-device interactions appear to be a primary source of lost recording performance. The current state of the art for visualizing the tissue response surrounding brain implants in animals is Immunohistochemistry + Confocal Microscopy, which is mainly performed after sacrificing the animal. Monitoring the tissue response as it develops could reveal important features of the response which may inform improvements in electrode design. Optical Coherence Tomography (OCT), an imaging technique commonly used in ophthalmology, has already been adapted ...

In this study, an optical gain chip using emission-wavelength-controlled self-assembled InAs quantum dots (QDs) was developed for swept-source optical coherence tomography (SS-OCT) applications. The optical characterizations indicated that the QDs emission wavelength and optical gain spectra were controlled in the 1.1 μ m waveband by optimizing the QDs growth conditions. This waveband is useful for obtaining a large imaging depth of OCT because of an optimal balance between absorption and scattering in biological samples. In addition, continuous tunable lasing in the waveband was achieved by introducing the QD-based gain chip into a grating-coupled external cavity. This tunable laser was introduced ...

Optical coherence elastography based on the measurements of elastic wave speeds can quantify elastic moduli in the wave propagation directions and provide high-resolution elasticity maps for tissue. Here, we simultaneously visualized a longitudinal shear wave propagating along the depth and a Rayleigh wave propagating in the lateral direction, and analyzed the propagation characteristics of the elastic waves, including group speeds, frequency spectra, and frequency-dependent wave speeds. The analysis of the propagation characteristics demonstrates the reliability of the elasticity quantification by measuring different types of speeds of the elastic waves.

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 ...