Automated motion correction using parallel-strip registration for wide-field en face OCT angiogram

We propose an innovative registration method to correct motion artifacts for wide-field optical coherence tomography angiography (OCTA) acquired by ultrahigh-speed swept-source OCT (>200 kHz A-scan rate). Considering that the number of A-scans along the fast axis is much higher than the number of positions along slow axis in the wide-field OCTA scan, a non-orthogonal scheme is introduced. Two en face angiograms in the vertical priority (2 y-fast) are divided into microsaccade-free parallel strips. A gross registration based on large vessels and a fine registration based on small vessels are sequentially applied to register parallel strips into a composite image. This technique is extended to automatically montage individual registered, motion-free angiograms into an ultrawide-field view.

Automated fine structure image analysis method for discrimination of diabetic retinopathy stage using conjunctival microvasculature images

The conjunctiva is a densely vascularized mucus membrane covering the sclera of the eye with a unique advantage of accessibility for direct visualization and non-invasive imaging. The purpose of this study is to apply an automated quantitative method for discrimination of different stages of diabetic retinopathy (DR) using conjunctival microvasculature images. Fine structural analysis of conjunctival microvasculature images was performed by ordinary least square regression and Fisher linear discriminant analysis. Conjunctival images between groups of non-diabetic and diabetic subjects at different stages of DR were discriminated. The automated method's discriminate rates were higher than those determined by human observers. The method allowed sensitive and rapid discrimination by assessment of conjunctival microvasculature images and can be potentially useful for DR screening and monitoring.

Detection of retinal blood vessel changes in multiple sclerosis with optical coherence tomography

Although retinal vasculitis is common in multiple sclerosis (MS), it is not known if MS is associated with quantitative abnormalities in retinal blood vessels (BVs). Optical coherence tomography (OCT) is suitable for examining the integrity of the anterior visual pathways in MS. In this paper we have compared the size and number of retinal blood vessels in patients with MS, with and without a history of optic neuritis (ON), and control subjects from the cross-sectional retinal images from OCT. Blood vessel diameter (BVD), blood vessel number (BVN), and retinal nerve fiber layer thickness (RNFLT) were extracted from OCT images collected from around the optic nerves of 129 eyes (24 control, 24 MS + ON, 81 MS-ON) of 71 subjects. Associations between blood vessel metrics, MS diagnosis, MS disability, ON, and RNFLT were evaluated using generalized estimating equation (GEE) models. MS eyes had a lower total BVD and BVN than control eyes. The effect was more pronounced with increased MS disability, and persisted in multivariate models adjusting for RNFLT and ON history. Twenty-nine percent (29%) of MS subjects had fewer retinal blood vessels than all control subjects. MS diagnosis, disability, and ON history were not associated with average blood vessel size. The relationship between MS and lower total BVD/BVN is not accounted for by RNFLT or ON. Further study is needed to determine the relationship between OCT blood vessel metrics and qualitative retinal blood vessel abnormalities in MS.

Temporal binning of time-correlated single photon counting data improves exponential decay fits and imaging speed

Time-correlated single photon counting (TCSPC) enables acquisition of fluorescence lifetime decays with high temporal resolution within the fluorescence decay. However, many thousands of photons per pixel are required for accurate lifetime decay curve representation, instrument response deconvolution, and lifetime estimation, particularly for two-component lifetimes. TCSPC imaging speed is inherently limited due to the single photon per laser pulse nature and low fluorescence event efficiencies (<10%) required to reduce bias towards short lifetimes. Here, simulated fluorescence lifetime decays are analyzed by SPCImage and SLIM Curve software to determine the limiting lifetime parameters and photon requirements of fluorescence lifetime decays that can be accurately fit. Data analysis techniques to improve fitting accuracy for low photon count data were evaluated. Temporal binning of the decays from 256 time bins to 42 time bins significantly (p<0.0001) improved fit accuracy in SPCImage and enabled accurate fits with low photon counts (as low as 700 photons/decay), a 6-fold reduction in required photons and therefore improvement in imaging speed. Additionally, reducing the number of free parameters in the fitting algorithm by fixing the lifetimes to known values significantly reduced the lifetime component error from 27.3% to 3.2% in SPCImage (p<0.0001) and from 50.6% to 4.2% in SLIM Curve (p<0.0001). Analysis of nicotinamide adenine dinucleotide-lactate dehydrogenase (NADH-LDH) solutions confirmed temporal binning of TCSPC data and a reduced number of free parameters improves exponential decay fit accuracy in SPCImage. Altogether, temporal binning (in SPCImage) and reduced free parameters are data analysis techniques that enable accurate lifetime estimation from low photon count data and enable TCSPC imaging speeds up to 6x and 300x faster, respectively, than traditional TCSPC analysis.

Automated volumetric segmentation of retinal fluid on optical coherence tomography

We propose a novel automated volumetric segmentation method to detect and quantify retinal fluid on optical coherence tomography (OCT). The fuzzy level set method was introduced for identifying the boundaries of fluid filled regions on B-scans (x and y-axes) and C-scans (z-axis). The boundaries identified from three types of scans were combined to generate a comprehensive volumetric segmentation of retinal fluid. Then, artefactual fluid regions were removed using morphological characteristics and by identifying vascular shadowing with OCT angiography obtained from the same scan. The accuracy of retinal fluid detection and quantification was evaluated on 10 eyes with diabetic macular edema. Automated segmentation had good agreement with manual segmentation qualitatively and quantitatively. The fluid map can be integrated with OCT angiogram for intuitive clinical evaluation.

Automatic differentiation of color fundus images containing drusen or exudates using a contextual spatial pyramid approach

We developed an automatic system to identify and differentiate color fundus images containing no lesions, drusen or exudates. Drusen and exudates are lesions with a bright appearance, associated with age-related macular degeneration and diabetic retinopathy, respectively. The system consists of three lesion detectors operating at pixel-level, combining their outputs using spatial pooling and classification with a random forest classifier. System performance was compared with ratings of two independent human observers using human-expert annotations as reference. Kappa agreements of 0.89, 0.97 and 0.92 and accuracies of 0.93, 0.98 and 0.95 were obtained for the system and observers, respectively.

Projection-resolved optical coherence tomographic angiography

Shadowgraphic projection artifacts from superficial vasculature interfere with the visualization of deeper vascular networks in optical coherence tomography angiography (OCT-A). We developed a novel algorithm to remove this artifact by resolving the ambiguity between in situ and projected flow signals. The algorithm identifies voxels with in situ flow as those where intensity-normalized decorrelation values are higher than all shallower voxels in the same axial scan line. This "projection-resolved" (PR) algorithm effectively suppressed the projection artifact on both en face and cross-sectional angiograms and enhanced depth resolution of vascular networks. In the human macula, the enhanced angiograms show three distinct vascular plexuses in the inner retina and no vessels in the outer retina. We demonstrate that PR OCT-A cleanly removes flow projection from the normally avascular outer retinal slab while preserving the density and continuity of the intermediate and deep retinal capillary plexuses.

Tissue thickness calculation in ocular optical coherence tomography

Thickness measurements derived from optical coherence tomography (OCT) images of the eye are a fundamental clinical and research metric, since they provide valuable information regarding the eye's anatomical and physiological characteristics, and can assist in the diagnosis and monitoring of numerous ocular conditions. Despite the importance of these measurements, limited attention has been given to the methods used to estimate thickness in OCT images of the eye. Most current studies employing OCT use an axial thickness metric, but there is evidence that axial thickness measures may be biased by tilt and curvature of the image. In this paper, standard axial thickness calculations are compared with a variety of alternative metrics for estimating tissue thickness. These methods were tested on a data set of wide-field chorio-retinal OCT scans (field of view (FOV) 60° x 25°) to examine their performance across a wide region of interest and to demonstrate the potential effect of curvature of the posterior segment of the eye on the thickness estimates. Similarly, the effect of image tilt was systematically examined with the same range of proposed metrics. The results demonstrate that image tilt and curvature of the posterior segment can affect axial tissue thickness calculations, while alternative metrics, which are not biased by these effects, should be considered. This study demonstrates the need to consider alternative methods to calculate tissue thickness in order to avoid measurement error due to image tilt and curvature.

In vivo imaging of retinal hemodynamics with OCT angiography and Doppler OCT

Retinal hemodynamics is important for early diagnosis and precise monitoring in retinal vascular diseases. We propose a novel method for measuring absolute retinal blood flow in vivo using the combined techniques of optical coherence tomography (OCT) angiography and Doppler OCT. Doppler values can be corrected by Doppler angles extracted from OCT angiography images. A three-dimensional (3D) segmentation algorithm based on dynamic programming was developed to extract the 3D boundaries of optic disc vessels, and Doppler angles were calculated from 3D vessel geometry. The accuracy of blood flow from the Doppler OCT was validated using a flow phantom. The feasibility of the method was tested on a subject in vivo. The pulsatile retinal blood flow and the parameters for retinal hemodynamics were successfully obtained.

Fully distributed absolute blood flow velocity measurement for middle cerebral arteries using Doppler optical coherence tomography

Doppler optical coherence tomography (DOCT) is considered one of the most promising functional imaging modalities for neuro biology research and has demonstrated the ability to quantify cerebral blood flow velocity at a high accuracy. However, the measurement of total absolute blood flow velocity (BFV) of major cerebral arteries is still a difficult problem since it is related to vessel geometry. In this paper, we present a volumetric vessel reconstruction approach that is capable of measuring the absolute BFV distributed along the entire middle cerebral artery (MCA) within a large field-of-view. The Doppler angle at each point of the MCA, representing the vessel geometry, is derived analytically by localizing the artery from pure DOCT images through vessel segmentation and skeletonization. Our approach could achieve automatic quantification of the fully distributed absolute BFV across different vessel branches. Experiments on rodents using swept-source optical coherence tomography showed that our approach was able to reveal the consequences of permanent MCA occlusion with absolute BFV measurement.

OCT-based crystalline lens topography in accommodating eyes

Custom Spectral Domain Optical Coherence Tomography (SD-OCT) provided with automatic quantification and distortion correction algorithms was used to measure anterior and posterior crystalline lens surface elevation in accommodating eyes and to evaluate relationships between anterior segment surfaces. Nine young eyes were measured at different accommodative demands. Anterior and posterior lens radii of curvature decreased at a rate of 0.78 ± 0.18 and 0.13 ± 0.07 mm/D, anterior chamber depth decreased at 0.04 ± 0.01 mm/D and lens thickness increased at 0.04 ± 0.01 mm/D with accommodation. Three-dimensional surface elevations were estimated by subtracting best fitting spheres. In the relaxed state, the spherical term accounted for most of the surface irregularity in the anterior lens (47%) and astigmatism (70%) in the posterior lens. However, in accommodated lenses astigmatism was the predominant surface irregularity (90%) in the anterior lens. The RMS of high-order irregularities of the posterior lens surface was statistically significantly higher than that of the anterior lens surface (x2.02, p<0.0001). There was significant negative correlation in vertical coma (Z3 (-1)) and oblique trefoil (Z3 (-3)) between lens surfaces. The astigmatic angle showed high degree of alignment between corneal surfaces, moderate between corneal and anterior lens surface (~27 deg), but differed by ~80 deg between the anterior and posterior lens surfaces (including relative anterior/posterior lens astigmatic angle shifts (10-20 deg).

Polarization microscopy for characterizing fiber orientation of ocular tissues

Characterizing the collagen fiber orientation and organization in the eye is necessary for a complete understanding of ocular biomechanics. In this study, we assess the performance of polarized light microscopy to determine collagen fiber orientation of ocular tissues. Our results demonstrate that the method provides objective, accurate, repeatable and robust data on fiber orientation with µm-scale resolution over a broad, cm-scale, field of view, unaffected by formalin fixation, without requiring tissue dehydration, labeling or staining. Together, this shows that polarized light microscopy is a powerful method for studying collagen architecture in the eye, with applications ranging from normal physiology and aging, to pathology and transplantation.

Advanced image processing for optical coherence tomographic angiography of macular diseases

This article provides an overview of advanced image processing for three dimensional (3D) optical coherence tomographic (OCT) angiography of macular diseases, including age-related macular degeneration (AMD) and diabetic retinopathy (DR). A fast automated retinal layers segmentation algorithm using directional graph search was introduced to separates 3D flow data into different layers in the presence of pathologies. Intelligent manual correction methods are also systematically addressed which can be done rapidly on a single frame and then automatically propagated to full 3D volume with accuracy better than 1 pixel. Methods to visualize and analyze the abnormalities including retinal and choroidal neovascularization, retinal ischemia, and macular edema were presented to facilitate the clinical use of OCT angiography.

Dynamic heart rate estimation using principal component analysis

In this paper, facial images from various video sequences are used to obtain a heart rate reading. In this study, a video camera is used to capture the facial images of eight subjects whose heart rates vary dynamically, between 81 and 153 BPM. Principal component analysis (PCA) is used to recover the blood volume pulses (BVP) which can be used for the heart rate estimation. An important consideration for accuracy of the dynamic heart rate estimation is to determine the shortest video duration that realizes it. This video duration is chosen when the six principal components (PC) are least correlated amongst them. When this is achieved, the first PC is used to obtain the heart rate. The results obtained from the proposed method are compared to the readings obtained from the Polar heart rate monitor. Experimental results show the proposed method is able to estimate the dynamic heart rate readings using less computational requirements when compared to the existing method. The mean absolute error and the standard deviation of the absolute errors between experimental readings and actual readings are 2.18 BPM and 1.71 BPM respectively.

Automatic neuron segmentation and neural network analysis method for phase contrast microscopy images

Phase Contrast Microscopy (PCM) is an important tool for the long term study of living cells. Unlike fluorescence methods which suffer from photobleaching of fluorophore or dye molecules, PCM image contrast is generated by the natural variations in optical index of refraction. Unfortunately, the same physical principles which allow for these studies give rise to complex artifacts in the raw PCM imagery. Of particular interest in this paper are neuron images where these image imperfections manifest in very different ways for the two structures of specific interest: cell bodies (somas) and dendrites. To address these challenges, we introduce a novel parametric image model using the level set framework and an associated variational approach which simultaneously restores and segments this class of images. Using this technique as the basis for an automated image analysis pipeline, results for both the synthetic and real images validate and demonstrate the advantages of our approach.

Semi-automated discrimination of retinal pigmented epithelial cells in two-photon fluorescence images of mouse retinas

Automated image segmentation is a critical step toward achieving a quantitative evaluation of disease states with imaging techniques. Two-photon fluorescence microscopy (TPM) has been employed to visualize the retinal pigmented epithelium (RPE) and provide images indicating the health of the retina. However, segmentation of RPE cells within TPM images is difficult due to small differences in fluorescence intensity between cell borders and cell bodies. Here we present a semi-automated method for segmenting RPE cells that relies upon multiple weak features that differentiate cell borders from the remaining image. These features were scored by a search optimization procedure that built up the cell border in segments around a nucleus of interest. With six images used as a test, our method correctly identified cell borders for 69% of nuclei on average. Performance was strongly dependent upon increasing retinosome content in the RPE. TPM image analysis has the potential of providing improved early quantitative assessments of diseases affecting the RPE.

Dynamic heart rate measurements from video sequences

This paper shows how dynamic heart rate measurements that are typically obtained from sensors mounted near to the heart can also be obtained from video sequences. In this study, two experiments are carried out where a video camera captures the facial images of the seven subjects. The first experiment involves the measurement of subjects' increasing heart rates (79 to 150 beats per minute (BPM)) while cycling whereas the second involves falling heart beats (153 to 88 BPM). In this study, independent component analysis (ICA) is combined with mutual information to ensure accuracy is not compromised in the use of short video duration. While both experiments are going on measures of heartbeat using the Polar heart rate monitor is also taken to compare with the findings of the proposed method. Overall experimental results show the proposed method can be used to measure dynamic heart rates where the root mean square error (RMSE) and the correlation coefficient are 1.88 BPM and 0.99 respectively.

Mapping conduction velocity of early embryonic hearts with a robust fitting algorithm

Cardiac conduction maturation is an important and integral component of heart development. Optical mapping with voltage-sensitive dyes allows sensitive measurements of electrophysiological signals over the entire heart. However, accurate measurements of conduction velocity during early cardiac development is typically hindered by low signal-to-noise ratio (SNR) measurements of action potentials. Here, we present a novel image processing approach based on least squares optimizations, which enables high-resolution, low-noise conduction velocity mapping of smaller tubular hearts. First, the action potential trace measured at each pixel is fit to a curve consisting of two cumulative normal distribution functions. Then, the activation time at each pixel is determined based on the fit, and the spatial gradient of activation time is determined with a two-dimensional (2D) linear fit over a square-shaped window. The size of the window is adaptively enlarged until the gradients can be determined within a preset precision. Finally, the conduction velocity is calculated based on the activation time gradient, and further corrected for three-dimensional (3D) geometry that can be obtained by optical coherence tomography (OCT). We validated the approach using published activation potential traces based on computer simulations. We further validated the method by adding artificially generated noise to the signal to simulate various SNR conditions using a curved simulated image (digital phantom) that resembles a tubular heart. This method proved to be robust, even at very low SNR conditions (SNR = 2-5). We also established an empirical equation to estimate the maximum conduction velocity that can be accurately measured under different conditions (e.g. sampling rate, SNR, and pixel size). Finally, we demonstrated high-resolution conduction velocity maps of the quail embryonic heart at a looping stage of development.

Localization of cortical tissue optical changes during seizure activity in vivo with optical coherence tomography

Optical coherence tomography (OCT) is a high resolution, minimally invasive imaging technique, which can produce depth-resolved cross-sectional images. In this study, OCT was used to detect changes in the optical properties of cortical tissue in vivo in mice during the induction of global (pentylenetetrazol) and focal (4-aminopyridine) seizures. Through the use of a confidence interval statistical method on depth-resolved volumes of attenuation coefficient, we demonstrated localization of regions exhibiting both significant positive and negative changes in attenuation coefficient, as well as differentiating between global and focal seizure propagation.

Feasibility of level-set analysis of enface OCT retinal images in diabetic retinopathy

Pathology segmentation in retinal images of patients with diabetic retinopathy is important to help better understand disease processes. We propose an automated level-set method with Fourier descriptor-based shape priors. A cost function measures the difference between the current and expected output. We applied our method to enface images generated for seven retinal layers and determined correspondence of pathologies between retinal layers. We compared our method to a distance-regularized level set method and show the advantages of using well-defined shape priors. Results obtained allow us to observe pathologies across multiple layers and to obtain metrics that measure the co-localization of pathologies in different layers.

Measuring the optical characteristics of medulloblastoma with optical coherence tomography

Medulloblastoma is the most common malignant pediatric brain tumor. Standard treatment consists of surgical resection, followed by radiation and high-dose chemotherapy. Despite these efforts, recurrence is common, leading to reduced patient survival. Even with successful treatment, there are often severe long-term neurologic impacts on the developing nervous system. We present two quantitative techniques that use a high-resolution optical imaging modality: optical coherence tomography (OCT) to measure refractive index, and the optical attenuation coefficient. To the best of our knowledge, this study is the first to demonstrate OCT analysis of medulloblastoma. Refractive index and optical attenuation coefficient were able to differentiate between normal brain tissue and medulloblastoma in mouse models. More specifically, optical attenuation coefficient imaging of normal cerebellum displayed layers of grey matter and white matter, which were indistinguishable in the structural OCT image. The morphology of the tumor was distinct in the optical attenuation coefficient imaging. These inherent properties may be useful during neurosurgical intervention to better delineate tumor boundaries and minimize resection of normal tissue.

Differential diagnosis of human bladder mucosa pathologies in vivo with cross-polarization optical coherence tomography

Quantitative image analysis and parameter extraction using a specific implementation of polarization-sensitive optical coherence tomography (OCT) provides differential diagnosis of mucosal pathologies in in-vivo human bladders. We introduce a cross-polarization (CP) OCT image metric called Integral Depolarization Factor (IDF) to enable automatic diagnosis of bladder conditions (assessment the functional state of collagen fibers). IDF-based diagnostic accuracy of identification of the severe fibrosis of normal bladder mucosa is 79%; recurrence of carcinoma on the post-operative scar is 97%; and differentiation between neoplasia and acute inflammation is 75%. The promising potential of CP OCT combined with image analysis in human urology is thus demonstrated in vivo.

Optical metabolic imaging quantifies heterogeneous cell populations

The genetic and phenotypic heterogeneity of cancers can contribute to tumor aggressiveness, invasion, and resistance to therapy. Fluorescence imaging occupies a unique niche to investigate tumor heterogeneity due to its high resolution and molecular specificity. Here, heterogeneous populations are identified and quantified by combined optical metabolic imaging and subpopulation analysis (OMI-SPA). OMI probes the fluorescence intensities and lifetimes of metabolic enzymes in cells to provide images of cellular metabolism, and SPA models cell populations as mixed Gaussian distributions to identify cell subpopulations. In this study, OMI-SPA is characterized by simulation experiments and validated with cell experiments. To generate heterogeneous populations, two breast cancer cell lines, SKBr3 and MDA-MB-231, were co-cultured at varying proportions. OMI-SPA correctly identifies two populations with minimal mean and proportion error using the optical redox ratio (fluorescence intensity of NAD(P)H divided by the intensity of FAD), mean NAD(P)H fluorescence lifetime, and OMI index. Simulation experiments characterized the relationships between sample size, data standard deviation, and subpopulation mean separation distance required for OMI-SPA to identify subpopulations.

Non-contact estimation of heart rate and oxygen saturation using ambient light

We propose a robust method for automated computation of heart rate (HR) from digital color video recordings of the human face. In order to extract photoplethysmographic signals, two orthogonal vectors of RGB color space are used. We used a dual tree complex wavelet transform based denoising algorithm to reduce artifacts (e.g. artificial lighting, movement, etc.). Most of the previous work on skin color based HR estimation performed experiments with healthy volunteers and focused to solve motion artifacts. In addition to healthy volunteers we performed experiments with child patients in pediatric intensive care units. In order to investigate the possible factors that affect the non-contact HR monitoring in a clinical environment, we studied the relation between hemoglobin levels and HR estimation errors. Low hemoglobin causes underestimation of HR. Nevertheless, we conclude that our method can provide acceptable accuracy to estimate mean HR of patients in a clinical environment, where the measurements can be performed remotely. In addition to mean heart rate estimation, we performed experiments to estimate oxygen saturation. We observed strong correlations between our SpO2 estimations and the commercial oximeter readings.

Quantifying the vascular response to ischemia with speckle variance optical coherence tomography

Longitudinal monitoring techniques for preclinical models of vascular remodeling are critical to the development of new therapies for pathological conditions such as ischemia and cancer. In models of skeletal muscle ischemia in particular, there is a lack of quantitative, non-invasive and long term assessment of vessel morphology. Here, we have applied speckle variance optical coherence tomography (OCT) methods to quantitatively assess vascular remodeling and growth in a mouse model of peripheral arterial disease. This approach was validated on two different mouse strains known to have disparate rates and abilities of recovering following induction of hind limb ischemia. These results establish the potential for speckle variance OCT as a tool for quantitative, preclinical screening of pro- and anti-angiogenic therapies.