Showing papers on "Optical coherence tomography published in 2018"

Nano-optic endoscope for high-resolution optical coherence tomography in vivo

Abstract: Acquisition of high-resolution images from within internal organs using endoscopic optical imaging has numerous clinical applications. However, difficulties associated with optical aberrations and the trade-off between transverse resolution and depth-of-focus significantly limit the scope of applications. Here, we integrate a metalens, with the ability to modify the phase of incident light at sub-wavelength level, into the design of an endoscopic optical coherence tomography catheter (termed nano-optic endoscope) to achieve near diffraction-limited imaging through negating non-chromatic aberrations. Remarkably, the tailored chromatic dispersion of the metalens in the context of spectral interferometry is utilized to maintain high-resolution imaging beyond the input field Rayleigh range, easing the trade-off between transverse resolution and depth-of-focus. We demonstrate endoscopic imaging both in resected human lung specimens and in sheep airways in vivo. The combination of the superior resolution and higher imaging depth-of-focus of the nano-optic endoscope will likely increase the clinical utility of endoscopic optical imaging.

DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images

Abstract: Given that the neural and connective tissues of the optic nerve head (ONH) exhibit complex morphological changes with the development and progression of glaucoma, their simultaneous isolation from optical coherence tomography (OCT) images may be of great interest for the clinical diagnosis and management of this pathology. A deep learning algorithm (custom U-NET) was designed and trained to segment 6 ONH tissue layers by capturing both the local (tissue texture) and contextual information (spatial arrangement of tissues). The overall Dice coefficient (mean of all tissues) was 0.91 ± 0.05 when assessed against manual segmentations performed by an expert observer. Further, we automatically extracted six clinically relevant neural and connective tissue structural parameters from the segmented tissues. We offer here a robust segmentation framework that could also be extended to the 3D segmentation of the ONH tissues.

AI for medical imaging goes deep.

Abstract: An artificial intelligence (AI) using a deep-learning approach can classify retinal images from optical coherence tomography for early diagnosis of retinal diseases and has the potential to be used in other image-based medical diagnoses.

Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors.

Abstract: An optical technique called line-field confocal optical coherence tomography (LC-OCT) is introduced for high-resolution, noninvasive imaging of human skin in vivo. LC-OCT combines the principles of time-domain optical coherence tomography and confocal microscopy with line illumination and detection using a broadband laser and a line-scan camera. LC-OCT measures the echo-time delay and amplitude of light backscattered from cutaneous microstructures through low-coherence interferometry associated with confocal spatial filtering. Multiple A-scans are acquired simultaneously while dynamically adjusting the focus. The resulting cross-sectional B-scan image is produced in real time at 10 frame / s. With an isotropic spatial resolution of ∼1 μm, the LC-OCT images reveal a comprehensive structural mapping of skin at the cellular level down to a depth of ∼500 μm. LC-OCT has been applied to the imaging of various skin lesions, in vivo, including carcinomas and melanomas. LC-OCT images are found to strongly correlate with conventional histopathological images. The use of LC-OCT as an adjunct tool in medical practice could significantly improve clinical diagnostic accuracy while reducing the number of biopsies of benign lesions.

Deep learning approach for the detection and quantification of intraretinal cystoid fluid in multivendor optical coherence tomography.

Abstract: We developed a deep learning algorithm for the automatic segmentation and quantification of intraretinal cystoid fluid (IRC) in spectral domain optical coherence tomography (SD-OCT) volumes independent of the device used for acquisition. A cascade of neural networks was introduced to include prior information on the retinal anatomy, boosting performance significantly. The proposed algorithm approached human performance reaching an overall Dice coefficient of 0.754 ± 0.136 and an intraclass correlation coefficient of 0.936, for the task of IRC segmentation and quantification, respectively. The proposed method allows for fast quantitative IRC volume measurements that can be used to improve patient care, reduce costs, and allow fast and reliable analysis in large population studies.

Speckle noise reduction in optical coherence tomography images based on edge-sensitive cGAN.

Abstract: Speckle noise in optical coherence tomography (OCT) impairs both the visual quality and the performance of automatic analysis. Edge preservation is an important issue for speckle reduction. In this paper, we propose an end-to-end framework for simultaneous speckle reduction and contrast enhancement for retinal OCT images based on the conditional generative adversarial network (cGAN). The edge loss function is added to the final objective so that the model is sensitive to the edge-related details. We also propose a novel method for obtaining clean images for training from outputs of commercial OCT scanners. The results show that the overall denoising performance of the proposed method is better than other traditional methods and deep learning methods. The proposed model also has good generalization ability and is capable of despeckling different types of retinal OCT images.

Octave-spanning coherent supercontinuum generation in silicon on insulator from 1.06 μm to beyond 2.4 μm

Abstract: Efficient complementary metal-oxide semiconductor-based nonlinear optical devices in the near-infrared are in strong demand. Due to two-photon absorption in silicon, however, much nonlinear research is shifting towards unconventional photonics platforms. In this work, we demonstrate the generation of an octave-spanning coherent supercontinuum in a silicon waveguide covering the spectral region from the near- to shortwave-infrared. With input pulses of 18 pJ in energy, the generated signal spans the wavelength range from the edge of the silicon transmission window, approximately 1.06 to beyond 2.4 μm, with a −20 dB bandwidth covering 1.124–2.4 μm. An octave-spanning supercontinuum was also observed at the energy levels as low as 4 pJ (−35 dB bandwidth). We also measured the coherence over an octave, obtaining , in good agreement with the simulations. In addition, we demonstrate optimization of the third-order dispersion of the waveguide to strengthen the dispersive wave and discuss the advantage of having a soliton at the long wavelength edge of an octave-spanning signal for nonlinear applications. This research paves the way for applications, such as chip-scale precision spectroscopy, optical coherence tomography, optical frequency metrology, frequency synthesis and wide-band wavelength division multiplexing in the telecom window. A silicon-based source that generates a wide spectrum of light, spanning the near-infrared transparency window of silicon, has been made. Supercontinuum generation involves using short, high-power pulses to generate broad continuous spectra by propagating them through nonlinear media. Supercontinuum sources are needed for applications in spectroscopy and optical coherence tomography. Silicon is an attractive medium since it is compatible with standard semiconductor fabrication processes but it suffers from losses due to nonlinear processes such as two-photon absorption. Now, Neetesh Singh of Massachusetts Institute of Technology in the USA and co-workers have realized a fully coherent supercontinuum generation in a silicon waveguide over a full octave that spans the near to shortwave infrared window. The researchers envision their source being used in applications such as chip-scale precision spectroscopy, optical frequency metrology and optical communications.

Optical coherence tomography angiography: a review of current and future clinical applications.

Abstract: Optical coherence tomography angiography is a non-invasive imaging technique that now allows for simultaneous in vivo imaging of the morphology as well as the vasculature in the eye. In this review, we provide an update on the existing clinical applications of optical coherence tomography angiography technology from the anterior to posterior segment of the eye. We also discuss the limitations of optical coherence tomography angiography technology, as well as the caveats to the interpretation of images. As current optical coherence tomography angiography systems are optimized for the retina, most studies have focused on interpreting images from conditions such as age related macular degeneration and retinal vascular diseases. However, the interpretation of these optical coherence tomography angiography images should be taken in consideration with other multi-modal imaging to overcome the limitations of each technique. In addition, there are a growing variety of clinical applications for optical coherence tomography angiography imaging in optic nerve head evaluation for glaucoma and optic neuropathies. Further developments in anterior optical coherence tomography angiography have now allowed for evaluation of anterior segment pathology such as glaucoma, ocular surface diseases, corneal vascularisation, and abnormal iris vasculature. Future developments in software could allow for improved segmentation and image resolution with automated measurements and analysis.

Measurement of tissue optical properties in the context of tissue optical clearing

Abstract: Nowadays, dynamically developing optical (photonic) technologies play an ever-increasing role in medicine. Their adequate and effective implementation in diagnostics, surgery, and therapy needs reliable data on optical properties of human tissues, including skin. This paper presents an overview of recent results on the measurements and control of tissue optical properties. The issues reported comprise a brief review of optical properties of biological tissues and efficacy of optical clearing (OC) method in application to monitoring of diabetic complications and visualization of blood vessels and microcirculation using a number of optical imaging technologies, including spectroscopic, optical coherence tomography, and polarization- and speckle-based ones. Molecular modeling of immersion OC of skin and specific technique of OC of adipose tissue by its heating and photodynamic treatment are also discussed.

Advances in optical coherence tomography in dermatology-a review.

Abstract: Optical coherence tomography (OCT) was introduced as an imaging system, but like ultrasonography, other measures, such as blood perfusion and polarization of light, have enabled the technology to approach clinical utility. This review aims at providing an overview of the advances in clinical research based on the improving technical aspects. OCT provides cross-sectional and en face images down to skin depths of 0.4 to 2.00 mm with optical resolution of 3 to 15 μm. Dynamic optical coherence tomography (D-OCT) enables the visualization of cutaneous microvasculature via detection of rapid changes in the interferometric signal of blood flow. Nonmelanoma skin cancer (NMSC) is the most comprehensively investigated topic, resulting in improved descriptions of morphological features and diagnostic criteria. A refined scoring system for diagnosing NMSC, taking findings from conventional and D-OCT into account, is warranted. OCT diagnosis of melanoma is hampered by the resolution and the optical properties of melanin. D-OCT may be of value in diseases characterized with dynamic changes in the vasculature of the skin and the addition of functional measures is strongly encouraged. In conclusion, OCT in dermatology is still an emerging technology that has great potential for improving further in the future.

Deep Learning-Based Automated Classification of Multi-Categorical Abnormalities From Optical Coherence Tomography Images.

Abstract: Purpose To develop a new intelligent system based on deep learning for automatically optical coherence tomography (OCT) images categorization. Methods A total of 60,407 OCT images were labeled by 17 licensed retinal experts and 25,134 images were included. One hundred one-layer convolutional neural networks (ResNet) were trained for the categorization. We applied 10-fold cross-validation method to train and optimize our algorithms. The area under the receiver operating characteristic curve (AUC), accuracy and kappa value were calculated to evaluate the performance of the intelligent system in categorizing OCT images. We also compared the performance of the system with results obtained by two experts. Results The intelligent system achieved an AUC of 0.984 with an accuracy of 0.959 in detecting macular hole, cystoid macular edema, epiretinal membrane, and serous macular detachment. Specifically, the accuracies in discriminating normal images, cystoid macular edema, serous macular detachment, epiretinal membrane, and macular hole were 0.973, 0.848, 0.947, 0.957, and 0.978, respectively. The system had a kappa value of 0.929, while the two physicians' kappa values were 0.882 and 0.889 independently. Conclusions This deep learning-based system is able to automatically detect and differentiate various OCT images with excellent accuracy. Moreover, the performance of the system is at a level comparable to or better than that of human experts. This study is a promising step in revolutionizing current disease diagnostic pattern and has the potential to generate a significant clinical impact. Translational relevance This intelligent system has great value in increasing retinal diseases' diagnostic efficiency in clinical circumstances.

A Deep Learning Approach to Digitally Stain Optical Coherence Tomography Images of the Optic Nerve Head.

Abstract: PURPOSE. To develop a deep learning approach to digitally stain optical coherence tomography (OCT) images of the optic nerve head (ONH). METHODS. A horizontal B-scan was acquired through the center of the ONH using OCT (Spectralis) for one eye of each of 100 subjects (40 healthy and 60 glaucoma). All images were enhanced using adaptive compensation. A custom deep learning network was then designed and trained with the compensated images to digitally stain (i.e., highlight) six tissue layers of the ONH. The accuracy of our algorithm was assessed (against manual segmentations) using the dice coefficient, sensitivity, specificity, intersection over union (IU), and accuracy. We studied the effect of compensation, number of training images, and performance comparison between glaucoma and healthy subjects. RESULTS. For images it had not yet assessed, our algorithm was able to digitally stain the retinal nerve fiber layer þ prelamina, the RPE, all other retinal layers, the choroid, and the peripapillary sclera and lamina cribrosa. For all tissues, the dice coefficient, sensitivity, specificity, IU, and accuracy (mean) were 0.84 6 0.03, 0.92 6 0.03, 0.99 6 0.00, 0.89 6 0.03, and 0.94 6 0.02, respectively. Our algorithm performed significantly better when compensated images were used for training (P < 0.001). Besides offering a good reliability, digital staining also performed well on OCT images of both glaucoma and healthy individuals. CONCLUSIONS. Our deep learning algorithm can simultaneously stain the neural and connective tissues of the ONH, offering a framework to automatically measure multiple key structural parameters of the ONH that may be critical to improve glaucoma management.

Optical coherence tomography in multiple sclerosis.

Abstract: To summarize recent findings regarding the utility of optical coherence tomography in multiple sclerosis. We searched PubMed for relevant articles using the keywords 'optical coherence tomography multiple sclerosis'. Additional articles were found via references in these articles. We selected articles based on relevance. Optical coherence tomography has contributed to greater insights into the pathophysiology of multiple sclerosis. Loss of retinal nerve fibre layer and ganglion cell layer thickness correlate with clinical and paraclinical parameters such as visual function, disability and magnetic resonance imaging. Some studies indicate that OCT parameters may be able to predict disability progression and visual function in MS. OCT angiography has recently emerged as a novel technique to study MS. OCT has proven very useful with regards to research, monitoring and predicting disability in multiple sclerosis. It will be interesting to see how OCT angiography will contribute to this field.

In vivo high resolution human corneal imaging using full-field optical coherence tomography.

Abstract: We present the first full-field optical coherence tomography (FFOCT) device capable of in vivo imaging of the human cornea. We obtained images of the epithelial structures, Bowman’s layer, sub-basal nerve plexus (SNP), anterior and posterior stromal keratocytes, stromal nerves, Descemet’s membrane and endothelial cells with visible nuclei. Images were acquired with a high lateral resolution of 1.7 µm and relatively large field-of-view of 1.26 mm x 1.26 mm – a combination, which, to the best of our knowledge, has not been possible with other in vivo human eye imaging methods. The latter together with a contactless operation, make FFOCT a promising candidate for becoming a new tool in ophthalmic diagnostics.

Vector method for strain estimation in phase-sensitive optical coherence elastography

Abstract: A noise-tolerant approach to strain estimation in phase-sensitive optical coherence elastography, robust to decorrelation distortions, is discussed. The method is based on evaluation of interframe phase-variation gradient, but its main feature is that the phase is singled out at the very last step of the gradient estimation. All intermediate steps operate with complex-valued optical coherence tomography (OCT) signals represented as vectors in the complex plane (hence, we call this approach the 'vector' method). In comparison with such a popular method as least-square fitting of the phase-difference slope over a selected region (even in the improved variant with amplitude weighting for suppressing small-amplitude noisy pixels), the vector approach demonstrates superior tolerance to both additive noise in the receiving system and speckle-decorrelation caused by tissue straining. Another advantage of the vector approach is that it obviates the usual necessity of error-prone phase unwrapping. Here, special attention is paid to modifications of the vector method that make it especially suitable for processing deformations with significant lateral inhomogeneity, which often occur in real situations. The method's advantages are demonstrated using both simulated and real OCT scans obtained during reshaping of a collagenous tissue sample irradiated by an IR laser beam producing complex spatially inhomogeneous deformations.

Optical coherence tomography angiography retinal vascular network assessment in multiple sclerosis.

Abstract: Background:Optical coherence tomography (OCT) angiography is a new method to assess the density of the vascular networks. Vascular abnormalities are considered involved in multiple sclerosis (MS) p...

Tunable optical coherence tomography in the infrared range using visible photons

Abstract: Optical coherence tomography (OCT) is an appealing technique for bio-imaging, medicine, and material analysis. For many applications, OCT in mid- and far-infrared (IR) leads to significantly more accurate results. Reported mid-IR OCT systems require light sources and photodetectors which operate in mid-IR range. These devices are expensive and need cryogenic cooling. Here, we report a proof-of-concept demonstration of a wavelength tunable IR OCT technique with detection of only visible range photons. Our method is based on the nonlinear interference of frequency correlated photon pairs. The nonlinear crystal, introduced in the Michelson-type interferometer, generates photon pairs with one photon in the visible and another in the IR range. The intensity of detected visible photons depends on the phase and loss of IR photons, which interact with the sample under study. This enables us to characterize sample properties and perform imaging in the IR range by detecting visible photons. The technique possesses broad wavelength tunability and yields a fair axial and lateral resolution, which can be tailored to the specific application. The work contributes to the development of versatile 3D imaging and material characterization systems working in a broad range of IR wavelengths, which do not require the use of IR-range light sources and photodetectors.

Retinal optical coherence tomography image enhancement via deep learning.

Abstract: Optical coherence tomography (OCT) images of the retina are a powerful tool for diagnosing and monitoring eye disease. However, they are plagued by speckle noise, which reduces image quality and reliability of assessment. This paper introduces a novel speckle reduction method inspired by the recent successes of deep learning in medical imaging. We present two versions of the network to reflect the needs and preferences of different end-users. Specifically, we train a convolution neural network to denoise cross-sections from OCT volumes of healthy eyes using either (1) mean-squared error, or (2) a generative adversarial network (GAN) with Wasserstein distance and perceptual similarity. We then interrogate the success of both methods with extensive quantitative and qualitative metrics on cross-sections from both healthy and glaucomatous eyes. The results show that the former approach provides state-of-the-art improvement in quantitative metrics such as PSNR and SSIM, and aids layer segmentation. However, the latter approach, which puts more weight on visual perception, outperformed for qualitative comparisons based on accuracy, clarity, and personal preference. Overall, our results demonstrate the effectiveness and efficiency of a deep learning approach to denoising OCT images, while maintaining subtle details in the images.

High-speed optical coherence tomography by circular interferometric ranging.

Abstract: Existing three-dimensional optical imaging methods excel in controlled environments but are difficult to deploy over large, irregular and dynamic fields. This has limited imaging in areas such as material inspection and medicine. To better address these applications, we developed methods in optical coherence tomography (OCT) to efficiently interrogate sparse scattering fields, i.e., those in which most locations (voxels) do not generate meaningful signal. Frequency comb sources are used to superimpose reflected signals from equispaced locations through optical subsampling. This results in circular ranging, and reduces the number of measurements required to interrogate large volumetric fields. As a result, signal acquisition barriers that have limited speed and field in OCT are avoided. With a new ultrafast, time-stretched frequency comb laser design operating with 7.6 MHz to 18.9 MHz repetition rates, we achieved imaging of multi-cm3 fields at up to 7.5 volumes per second.

Optical coherence tomography: A guide to interpretation of common macular diseases.

Abstract: Optical coherence tomography is a quick, non invasive and reproducible imaging tool for macular lesions and has become an essential part of retina practice. This review address the common protocols for imaging the macula, basics of image interpretation, features of common macular disorders with clues to differentiate mimickers and an introduction to choroidal imaging . It includes case examples and also a practical algorithm for interpretation.

High-resolution, in vivo multimodal photoacoustic microscopy, optical coherence tomography, and fluorescence microscopy imaging of rabbit retinal neovascularization

Abstract: Photoacoustic microscopy (PAM) is an emerging imaging technology that can non-invasively visualize ocular structures in animal eyes. This report describes an integrated multimodality imaging system that combines PAM, optical coherence tomography (OCT), and fluorescence microscopy (FM) to evaluate angiogenesis in larger animal eyes. High-resolution in vivo imaging was performed in live rabbit eyes with vascular endothelial growth factor (VEGF)-induced retinal neovascularization (RNV). The results demonstrate that our multimodality imaging system can non-invasively visualize RNV in both albino and pigmented rabbits to determine retinal pathology using PAM and OCT and verify the leakage of neovascularization using FM and fluorescein dye. This work presents high-resolution visualization of angiogenesis in rabbits using a multimodality PAM, OCT, and FM system and may represent a major step toward the clinical translation of the technology.

Choroidal thickness in diabetic retinopathy assessed with swept-source optical coherence tomography.

Abstract: Purpose:To compare the choroidal thickness (CT) of diabetic eyes (different stages of disease) with controls, using swept-source optical coherence tomography.Methods:A multicenter, prospective, cross-sectional study of diabetic and nondiabetic subjects using swept-source optical coherence tomography

Trans-retinal cellular imaging with multimodal adaptive optics

Abstract: Adaptive optics (AO), when coupled to different imaging modalities, has enabled resolution of various cell types across the entire retinal depth in the living human eye. Extraction of information from retinal cells is optimal when their optical properties, structure, and physiology are matched to the unique capabilities of each imaging modality. Despite the earlier success of multimodal AO (mAO) approaches, the full capabilities of the individual imaging modalities were often diminished rather than enhanced when integrated into multimodal platforms. Furthermore, many mAO designs added unnecessary complexity, making clinical translation difficult. In this study, we present a novel mAO system that combines two complementary approaches, scanning laser ophthalmoscopy (SLO) and optical coherence tomography (OCT), in one instrument using a simplified optical design, flexible alternation of scanning modes, and independent focus control. The mAO system imaging performance was demonstrated by visualization of cells in their mosaic arrangement across the full depth of the retina in three human subjects, including microglia, nerve fiber bundles, retinal ganglion cells and axons, and capillaries in the inner retina and foveal cones, peripheral rods, and retinal pigment epithelial cells in the outer retina. Multimodal AO is a powerful tool to capture the most complete picture of retinal health.

Optic axis mapping with catheter-based polarization-sensitive optical coherence tomography

Abstract: Birefringence offers an intrinsic contrast mechanism related to the microstructure and arrangement of fibrillary tissue components. Here we present a reconstruction strategy to recover not only the scalar amount of birefringence, but also its optic axis orientation as a function of depth in tissue from measurements with catheter-based polarization-sensitive optical coherence tomography. A polarization symmetry constraint, intrinsic to imaging in the backscatter direction, facilitates the required compensation for wavelength-dependent transmission through the system elements, the rotating catheter, and overlying tissue layers. Applied to the intravascular imaging of coronary atherosclerosis in human patients, the optic axis affords refined interpretation of plaque architecture.

Near-infrared and mid-infrared semiconductor broadband light emitters

Abstract: Semiconductor broadband light emitters have emerged as ideal and vital light sources for a range of biomedical sensing/imaging applications, especially for optical coherence tomography systems. Although near-infrared broadband light emitters have found increasingly wide utilization in these imaging applications, the requirement to simultaneously achieve both a high spectral bandwidth and output power is still challenging for such devices. Owing to the relatively weak amplified spontaneous emission, as a consequence of the very short non-radiative carrier lifetime of the inter-subband transitions in quantum cascade structures, it is even more challenging to obtain desirable mid-infrared broadband light emitters. There have been great efforts in the past 20 years to pursue high-efficiency broadband optical gain and very low reflectivity in waveguide structures, which are two key factors determining the performance of broadband light emitters. Here we describe the realization of a high continuous wave light power of >20 mW and broadband width of >130 nm with near-infrared broadband light emitters and the first mid-infrared broadband light emitters operating under continuous wave mode at room temperature by employing a modulation p-doped InGaAs/GaAs quantum dot active region with a ‘J’-shape ridge waveguide structure and a quantum cascade active region with a dual-end analogous monolithic integrated tapered waveguide structure, respectively. This work is of great importance to improve the performance of existing near-infrared optical coherence tomography systems and describes a major advance toward reliable and cost-effective mid-infrared imaging and sensing systems, which do not presently exist due to the lack of appropriate low-coherence mid-infrared semiconductor broadband light sources. Broadband semiconductor sources are ideal and vital light sources for optical coherence tomography systems. Achieving broadband light sources in the near-infrared simultaneously with high spectral bandwidth and output power is still challenging. In the mid-infrared region, it is difficult for quantum cascade materials to obtain desirable broadband light due to the relatively weak amplified spontaneous emission. Chun-Cai Hou of Suzhou Institute of Nano-tech and Nano-bionics and co-workers have developed a 1.2 μm continuous wave operating superluminescence source with simultaneously high light power and wide broadband width. More importantly, the team has first developed a 5 μm continuous wave operating mid-infrared superluminescence source at room temperature by using a quantum cascade active region and a dual-end emitting analogous monolithic integrated tapered waveguide structure. This work will bring a new opportunity towards optical coherence tomography systems.