Evaluation of clinical images is essential for diagnosis in many specialties. Therefore the development of computer vision algorithms to help analyze biomedical images will be important. In ophthalmology, optical coherence tomography (OCT) is critical for managing retinal conditions. We developed a convolutional neural network (CNN) that detects intraretinal fluid (IRF) on OCT in a manner indistinguishable from clinicians. Using 1,289 OCT images, the CNN segmented images with a 0.911 cross-validated Dice coefficient, compared with segmentations by experts. Additionally, the agreement between experts and between experts and CNN were similar. Our results reveal that CNN can be trained to ...

A high-efficiency lensless all-fiber probe for optical coherence tomography (OCT) is presented. The probe is composed of a segment of large-core multimode fiber (MMF), a segment of tapered MMF, and a length of single-mode fiber (SMF). A controllable output beam can be designed by a simple adjustment of its probe structure parameters (PSPs), instead of the selection of fibers with different optical parameters. A side-view probe with a diameter of 340 μm and a rigid length of 6.37 mm was fabricated, which provides an effective imaging range of ∼ 0.6    mm ∼0.6  mm with a full width at ...

We report on the development of a technique for differentiating between biological micro-objects using a rigorous, full-wave model of OCT image formation. We model an existing experimental prototype which uses OCT to interrogate a microfluidic chip containing the blood cells. A full-wave model is required since the technique uses light back-scattered by a scattering substrate, rather than by the cells directly. The light back-scattered by the substrate is perturbed upon propagation through the cells, which flow between the substrate and imaging system’s objective lens. We present the key elements of the 3D, Maxwell equation-based computational model, the key findings ...

Most reported photoacoustic ocular imaging work to date uses small animals, such as mice and rats, the eyeball sizes of which are less than one-third of those of humans, posing challenges for clinical translation. Here we developed a novel integrated photoacoustic microscopy (PAM) and optical coherence tomography (OCT) system for dual-modality chorioretinal imaging of larger animals, such as rabbits. The system has quantified lateral resolutions of 4.1 µm (PAM) and 3.8 µm (OCT), and axial resolutions of 37.0 µm (PAM) and 4.0 µm (OCT) at the focal plane of the objective. Experimental results in living rabbits ...

We present a novel framework combining convolutional neural networks (CNN) and graph search methods (termed as CNN-GS) for the automatic segmentation of nine layer boundaries on retinal optical coherence tomography (OCT) images. CNN-GS first utilizes a CNN to extract features of specific retinal layer boundaries and train a corresponding classifier to delineate a pilot estimate of the eight layers. Next, a graph search method uses the probability maps created from the CNN to find the final boundaries. We validated our proposed method on 60 volumes (2915 B-scans) from 20 human eyes with non-exudative age-related macular degeneration (AMD), which attested to ...

In this paper, we report what we believe is a novel technique to overcome the depth-of-focus (DOF) limitation in optical coherence tomography (OCT). Using confocal optics on a sample arm, we scanned the illumination beam across the under-filled objective lens pupil plane by steering the beam at the pinhole using a microcylindrical lens. The detected interferometric signals from multiple distinctive apertures were digitally refocused, which is analogous to synthetic aperture radar (SAR). Using numerical simulations and imaging experiments, we verified that this technique can maintain a diffraction-limited transverse resolution along a DOF that is ∼ 10 ∼10 times larger than the ...

The paper presents a proof-of-concept polarization-sensitive swept source optical coherence tomography (OCT) system that performs measurements of the retardance as well as of the axis orientation of a linear birefringent sample. The system performs single input state polarization-sensitive OCT and employs an optical module based on optically passive elements such as two beam displacers and a Faraday rotator. Our implementation of the PS-OCT system does not need any calibration step to compensate for the polarimetric effect of the fibers, and its operation does not require a balanced polarization-diversity detector. The optical module allows measurement of the two polarization properties of ...

Optical coherence tomography (OCT) has become one of the most successful optical technologies implemented in medicine and clinical practice mostly due to the possibility of non-invasive and non-contact imaging by detecting back-scattered light. OCT has gone through a tremendous development over the past 25 years. From its initial inception in 1991 [Science 254 , 1178 (1991)] it has become an indispensable medical imaging technology in ophthalmology. Also in fields like cardiology and gastro-enterology the technology is envisioned to become a standard of care. A key contributor to the success of OCT has been the sensitivity and speed advantage offered by Fourier ...

This feature issue commemorates the approximately 25 year history of Optical Coherence Tomography (OCT), one of the most successful biophotonic technologies. While OCT has technological origins traceable to ultrafast laser development and fiber optic system test instrumentation of the 1980’s, innovations in low coherence interferometry for optical ranging and imaging for biomedical applications in the U.S., Europe and Japan by the early 1990’s led to coinage of the now widely known term OCT in 1991 [1]. As discussed in the following cited Invited Review and Invited Research articles in this issue, remarkable strides have since been made ...

Recently, a new noncontact reflection-mode imaging modality called photoacoustic remote sensing (PARS) microscopy was introduced providing optical absorption contrast. Unlike previous modalities, which rely on interferometric detection of a probe beam to measure surface oscillations, the PARS technique detects photoacoustic initial pressures induced by a pulsed laser at their origin by monitoring intensity modulations of a reflected probe beam. In this paper, a model describing the temporal evolution from a finite excitation pulse is developed with consideration given to the coherence length of the interrogation beam. Analytical models are compared with approximations, finite-difference time-domain (FDTD) simulations, and experiments with good ...

We developed a fully automated system using a convolutional neural network (CNN) for total retina segmentation in optical coherence tomography (OCT) that is robust to the presence of severe retinal pathology. A generalized U-net network architecture was introduced to include the large context needed to account for large retinal changes. The proposed algorithm outperformed qualitative and quantitatively two available algorithms. The algorithm accurately estimated macular thickness with an error of 14.0 ± 22.1 µm, substantially lower than the error obtained using the other algorithms (42.9 ± 116.0 µm and 27.1 ± 69.3 µm, respectively). These results highlighted ...

We have developed dual-axis optical coherence tomography (DA-OCT) which enables deep tissue imaging by using a novel off-axis illumination/detection configuration. DA-OCT offers a 100-fold speed increase compared with its predecessor, multispectral multiple-scattering low coherence interferometry (ms2/LCI), by using a new beam scanning mechanism based on a microelectro-mechanical system (MEMS) mirror. The data acquisition scheme was altered to take advantage of this scanning speed, producing tomographic images at a rate of 4 frames (B-scans) per second. DA-OCT differs from ms2/LCI in that the dual axes intersect at a shallower depth ( ∼ 1    mm ∼1  mm ). This difference, coupled with ...

Basal cell carcinoma (BCC) and melanoma (MM), with the highest morbidity and mortality, respectively, are considered as two skin cancers of concern in dermatology. Histological studies have demonstrated that vascular patterns and collagenous stroma serve as key parameters for BCC and MM classification. In this Letter, we sought to identify BCC and MM based on the dual parameters of vascular patterns and scattering structures provided by all-optically integrated photoacoustic and optical coherence tomography (AOPA/OCT). The imaging capability of the AOPA/OCT was verified by the mimic phantoms. Furthermore, in vivo characterization of vasculatures and tissue structures from BCC and ...

This article introduces a method to extract the speed and density of microparticles in real time at several kHz using an asynchronous event-based camera mounted on a full-field optical coherence tomography (FF-OCT) setup. These cameras detect significant amplitude changes, allowing scene-driven acquisitions. They are composed of an array of autonomously operating pixels. Events are triggered when an illuminance change at the pixel level is significant at 1 μs time precision. The event-driven FF-OCT algorithm relies on a time-based optical flow computation to operate directly on incoming events and updates the estimation of velocity, direction and density while reducing both computation ...

We developed an algorithm to remove decorrelation noise due to bulk motion in optical coherence tomography angiography (OCTA) of the posterior eye. In this algorithm, OCTA B-frames were divided into segments within which the bulk motion velocity could be assumed to be constant. This velocity was recovered using linear regression of decorrelation versus the logarithm of reflectance in axial lines (A-lines) identified as bulk tissue by percentile analysis. The fitting parameters were used to calculate a reflectance-adjusted upper bound threshold for bulk motion decorrelation. Below this threshold, voxels are identified as non-flow tissue, their flow values are set to zeros ...

Conventional imaging of the human cornea with optical coherence tomography (OCT) relies on telecentric scanning optics with sampling beams that are parallel to the optical axis of the eye. Because of the shape of the cornea, the beams have in some areas considerable inclination to the corneal surface which is accompanied by low signal intensities in these areas and thus an inhomogeneous appearance of corneal structures. In addition, alterations in the polarization state of the probing light depend on the angle between the imaging beam and the birefringent axis of the sample. Therefore, changes in the polarization state observed with ...

Shortly after the first demonstration of optical coherence tomography for imaging the microstructure of the human eye, work began on developing systems and catheters suitable for intravascular imaging in order to diagnose and investigate atherosclerosis and potentially to monitor therapy. This review covers the driving considerations of the clinical application and its constraints, the major engineering milestones that enabled the current, high-performance commercial imaging systems, the key studies that laid the groundwork for image interpretation, and the clinical research that traces intravascular optical coherence tomography (OCT) from early human pilot studies to current clinical trials.

Optical coherence tomography (OCT) is based on coherence detection of interferometric signals and hence inevitably suffers from speckle noise. To remove speckle noise in OCT images, wavelet domain thresholding has demonstrated significant advantages in suppressing noise magnitude while preserving image sharpness. However, speckle noise in OCT images has different characteristics in different spatial scales, which has not been considered in previous applications of wavelet domain thresholding. In this study, we demonstrate a noise adaptive wavelet thresholding (NAWT) algorithm that exploits the difference of noise characteristics in different wavelet sub-bands. The algorithm is simple, fast, effective and is closely related to ...

A depth-dependent dispersion compensation algorithm for enhancing the image quality of the Fourier-domain optical coherence tomography (OCT) is presented. The dispersion related with depth in the sample is considered. Using the iterative method, an analytical formula for compensating the depth-dependent dispersion in the sample is obtained. We apply depth-dependent dispersion compensation algorithm to process the phantom images and in vivo images. Using sharpness metric based on variation coefficient to compare the results processed with different dispersion compensation algorithms, we find that the depth-dependent dispersion compensation algorithm can improve image quality at full depth.