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Purpose: To demonstrate the proper use of the Phansalkar local thresholding method (Phansalkar method) in choriocapillaris (CC) quantification with optical coherence tomography angiography (OCTA)., Design: Retrospective, observational case series., Methods: Swept source OCTA imaging was performed using 3×3 mm and 6×6 mm scanning patterns. The CC slab was extracted after semiautomatic segmentation of the retinal pigment epithelium/Bruch membrane complex. Retinal projection artifacts were removed before further analysis, and CC OCTA images from drusen eyes were compensated using a previously published strategy. CC flow deficits (FDs) were segmented with 2 previously published algorithms: the fuzzy C-means approach (FCM method) and the Phansalkar method. With the Phansalkar method, different parameters were tested and a local window radius of 1 to 15 pixels was used. FD density, mean FD size, and FD number were calculated for comparison., Results: Six normal eyes from 6 subjects and 6 eyes with drusen secondary to age-related macular degeneration from 6 subjects were analyzed. With both 3×3 mm and 6×6 mm scans from all eyes, the FD metrics were highly dependent on the selection of the local window radius when using the Phansalkar method. Larger window radii resulted in higher FD density values. FD number increased with the increase in the window radius but then decreased, with an inflection point at about 1 to 2 intercapillary distances. Mean FD size decreased then increased with increasing window radii., Conclusions: Multiple parameters, especially the local window radius, should be optimized before using the Phansalkar method for the quantification of CC FDs with OCTA imaging. It is recommended that the proper use of the Phansalkar method should include the selection of the window radius that is related to the expected intercapillary distance in normal eyes., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Cerebral ischemic stroke causes injury to brain tissue characterized by a complex cascade of neuronal and vascular events. Imaging during the early stages of its development allows prediction of tissue infarction and penumbra so that optimal intervention can be determined in order to salvage brain function impairment. Therefore, there is a critical need for novel imaging techniques that can characterize brain injury in the earliest phases of the ischemic stroke. This paper examined optical coherence tomography (OCT) for imaging acute injury in experimental ischemic stroke in vivo. Based on endogenous optical scattering signals provided by OCT imaging, we have developed a single, integrated imaging platform enabling the measurement of changes in blood perfusion, blood flow, erythrocyte velocity, and light attenuation within a cortical tissue, during focal cerebral ischemia in a mouse model. During the acute phase (from 5 min to the first few hours following the blood occlusion), the multi-parametric OCT imaging revealed multiple hemodynamic and tissue scattering responses in vivo, including cerebral blood flow deficits, capillary non-perfusion, displacement of penetrating vessels, and increased light attenuation in the cortical tissue at risk that are spatially correlated with the infarct core, as determined by postmortem staining with triphenyltetrazolium chloride. The use of multi-parametric OCT imaging may aid in the comprehensive evaluation of ischemic lesions during the early stages of stroke, thereby providing essential knowledge for guiding treatment decisions.

Choriocapillaris (CC) visualization and quantification remains challenging. We propose an innovative three-step registration and averaging approach using repeated swept source optical coherence tomography angiography (SS-OCTA) scans to conduct automatic quantitative assessment on CC. Six subjects were enrolled, each imaged at several locations with SS-OCTA from macular to equatorial regions using 3 mm × 3 mm scanning pattern. Five repeated volumes were collected for each subject. The complex optical microangiography (OMAG) algorithm was applied to identify blood flow in CC slab. An automatic three-step registration of translation, affine and B-Spline was applied to en face OCTA images of CC, followed with averaging. A fuzzy clustering approach was used to segment vasculature and flow deficits from the averaged images. The improvement in visualization of CC was evaluated and the average intercapillary distance was estimated by calculating the averaged capillary lumen spacing. A series of quantitative indices of flow deficit density, number, size, complexity index and aspect ratio index (FDD, FDN, FDS, FDCI and FDARI) were designed and validated with the increase of repeated scan numbers for averaging. Quantitative assessment was applied and compared on CC in macular and equatorial regions. The intercapillary distance was observed to be around 24 µm at macula and increased toward equatorial regions. All five quantitative indices (FDD, FDN, FDS, FDCI and FDARI) showed significant changes with multiple averaging and tend to become stable with repeated number of 4. Our proposed registration and averaging algorithm significantly improved the visualization of CC with SS-OCTA. The designed five indices for CC provide more options in the quantitative assessment of CC and are of great potentials in assisting the understanding of disease pathology, early diagnosis and treatment monitoring.

Optical coherence tomography angiography (OCTA) is increasingly becoming a popular inspection tool for biomedical imaging applications. By exploring the amplitude, phase and complex information available in OCT signals, numerous algorithms have been proposed that contrast functional vessel networks within microcirculatory tissue beds. However, it is not clear which algorithm delivers optimal imaging performance. Here, we investigate systematically how amplitude and phase information have an impact on the OCTA imaging performance, to establish the relationship of amplitude and phase stability with OCT signal-to-noise ratio (SNR), time interval and particle dynamics. With either repeated A-scan or repeated B-scan imaging protocols, the amplitude noise increases with the increase of OCT SNR; however, the phase noise does the opposite, i.e. it increases with the decrease of OCT SNR. Coupled with experimental measurements, we utilize a simple Monte Carlo (MC) model to simulate the performance of amplitude-, phase- and complex-based algorithms for OCTA imaging, the results of which suggest that complex-based algorithms deliver the best performance when the phase noise is  <  ~40 mrad. We also conduct a series of in vivo vascular imaging in animal models and human retina to verify the findings from the MC model through assessing the OCTA performance metrics of vessel connectivity, image SNR and contrast-to-noise ratio. We show that for all the metrics assessed, the complex-based algorithm delivers better performance than either the amplitude- or phase-based algorithms for both the repeated A-scan and the B-scan imaging protocols, which agrees well with the conclusion drawn from the MC simulations.

The ability to measure in vivo wall strain in embryonic hearts is important for fully understanding the mechanisms of cardiac development. Optical coherence tomography (OCT) is a powerful tool for the three-dimensional imaging of complex myocardial activities in early-stage embryonic hearts with high spatial and temporal resolutions. We describe a method to analyze periodic deformations of myocardial walls and evaluate in vivo myocardial wall strains with a high-speed spectral domain OCT system. We perform four-dimensional scanning on the outflow tract (OFT) of chick embryonic hearts and determine a special cross-section in which the OFT can be approximated as an annulus by analyzing Doppler blood-flow velocities. For each image acquired at the special cross-section, the annular myocardial wall is segmented with a semiautomatic boundary-detection algorithm, and the fluctuation myocardial wall thickness is calculated from the area and mean circumference of the myocardial wall. The experimental results shown with the embryonic chick hearts demonstrate that the proposed method is a useful tool for studying the biomechanical characteristics of embryonic hearts.

Optical coherence tomography (OCT)-based angiography is increasingly becoming a clinically useful and important imaging technique due to its ability to provide volumetric microvascular networks innervating tissue beds in vivo without a need for exogenous contrast agent. Numerous OCT angiography algorithms have recently been proposed for the purpose of contrasting microvascular networks. A general literature review is provided on the recent progress of OCT angiography methods and algorithms. The basic physics and mathematics behind each method together with its contrast mechanism are described. Potential directions for future technical development of OCT based angiography is then briefly discussed. Finally, by the use of clinical data captured from normal and pathological subjects, the imaging performance of vascular networks delivered by the most recently reported algorithms is evaluated and compared, including optical microangiography, speckle variance,phase variance, split-spectrum amplitude decorrelation angiography, and correlation mapping. It is found that the method that utilizes complex OCT signal to contrast retinal blood flow delivers the best performance among all the algorithms in terms of image contrast and vessel connectivity. The purpose of this review is to help readers understand and select appropriate OCT angiography algorithm for use in specific applications.

Optical coherence tomography (OCT) based microangiography is capable of visualizing 3D functional blood vessel networks within microcirculatory tissue beds in vivo. To provide the quantitative information of vasculature from the microangiograms such as vessel diameter and morphology, it is necessary to develop efficient vessel segmentation algorithms. In this paper, we propose to develop a hybrid Hessian/intensity based method to segment and quantify shape and diameter of the blood vessels innervating capillary beds that are imaged by functional OCT in vivo. The proposed method utilizes multi-scale Hessian filters to segment tubular structures such as blood vessels, but compounded by the intensity-based segmentation method to mitigate the limitations of Hessian filters' sensitivity to the selection of scale parameters. Such compounding segmentation scheme takes advantage of the morphological nature of Hessian filters while correcting for the scale parameter selection by intensity-based segmentation. The proposed algorithm is tested on a wound healing model and its performance of segmentation vessels is quantified by a publicly available manual segmentation dataset. We believe that this method will play an important role in the quantification of micro-angiograms for microcirculation research in ophthalmology and diagnosing retinal eye diseases involved with microcirculation., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method.

Optical coherence tomography (OCT) is a technique that allows for the three-dimensional (3D) imaging of small volumes of tissue (a few millimeters) with high resolution (∼10  μm). Optical microangiography (OMAG) is a method of processing OCT data, which allows for the extraction of the tissue vasculature with capillary resolution from the OCT images. Cross-sectional B-frame OMAG images present the location of the patent blood vessels; however, the signal-to-noise-ratio of these images can be affected by several factors such as the quality of the OCT system and the tissue motion artifact. This background noise can appear in the en face projection view image. In this work we propose to develop a binary mask that can be applied on the cross-sectional B-frame OMAG images, which will reduce the background noise while leaving the signal from the blood vessels intact. The mask is created by using a naïve Bayes (NB) classification algorithm trained with a gold standard image which is manually segmented by an expert. The masked OMAG images present better contrast for binarizing the image and quantifying the result without the influence of noise. The results are compared with a previously developed frequency rejection filter (FRF) method which is applied on the en face projection view image. It is demonstrated that both the NB and FRF methods provide similar vessel length fractions. The advantage of the NB method is that the results are applicable in 3D and that its use is not limited to periodic motion artifacts.

Optical microangiography (OMAG) is a method that enables the noninvasive extraction of blood vessels within biological tissues. OMAG B-frames are prone to noise; therefore, techniques such as B-frame averaging have been applied to reduce these effects. A drawback of this method is that the total acquisition time and amount of data collected are increased; hence, the data are susceptible to motion artifacts and decorrelation. In this paper we propose using an image filter on a nonaveraged OMAG B-frame to reduce its noise. Consequently, B-frames comparable to the averaged OMAG B-frame are obtained, while reducing the total acquisition and processing time. The method is tested with two different systems, a high-resolution spectral domain and a relatively low-resolution swept-source optical coherence tomography system. It is demonstrated that the weighted average filter produces the lowest B-frame error; however, all filters produce comparable results when quantifying the en face projection view image.

Lymphatic vessels are a part of the circulatory system that collect plasma and other substances that have leaked from the capillaries into interstitial fluid (lymph) and transport lymph back to the circulatory system. Since lymph is transparent, lymphatic vessels appear as dark hallow vessel-like regions in optical coherence tomography (OCT) cross sectional images. We propose an automatic method to segment lymphatic vessel lumen from OCT structural cross sections using eigenvalues of Hessian filters. Compared to the existing method based on intensity threshold, Hessian filters are more selective on vessel shape and less sensitive to intensity variations and noise. Using this segmentation technique along with optical micro-angiography allows label-free noninvasive simultaneous visualization of blood and lymphatic vessels in vivo. Lymphatic vessels play an important role in cancer, immune system response, inflammatory disease, wound healing and tissue regeneration. Development of imaging techniques and visualization tools for lymphatic vessels is valuable in understanding the mechanisms and studying therapeutic methods in related disease and tissue response.

Recent advances in optical coherence tomography (OCT), and the development of image reconstruction algorithms, enabled four-dimensional (4-D) (three-dimensional imaging over time) imaging of the embryonic heart. To further analyze and quantify the dynamics of cardiac beating, segmentation procedures that can extract the shape of the heart and its motion are needed. Most previous studies analyzed cardiac image sequences using manually extracted shapes and measurements. However, this is time consuming and subject to inter-operator variability. Automated or semi-automated analyses of 4-D cardiac OCT images, although very desirable, are also extremely challenging. This work proposes a robust algorithm to semi automatically detect and track cardiac tissue layers from 4-D OCT images of early (tubular) embryonic hearts. Our algorithm uses a two-dimensional (2-D) deformable double-line model (DLM) to detect target cardiac tissues. The detection algorithm uses a maximum-likelihood estimator and was successfully applied to 4-D in vivo OCT images of the heart outflow tract of day three chicken embryos. The extracted shapes captured the dynamics of the chick embryonic heart outflow tract wall, enabling further analysis of cardiac motion.

During cardiac development, the cardiac wall and flowing blood are two important cardiac tissues that constantly interact with each other. This dynamic interaction defines appropriate biomechanical environment to which the embryonic heart is exposed. Quantitative assessment of the dynamic parameters of wall tissues and blood flow is required to further our understanding of cardiac development. We report the use of an ultrafast 1310-nm dual-camera spectral domain optical coherence tomography (SDOCT) system to characterize/image, in parallel, the dynamic radial strain rate of the myocardial wall and the Doppler velocity of the underlying flowing blood within an in vivo beating chick embryo. The OCT system operates at 184-kHz line scan rate, providing the flexibility of imaging the fast blood flow and the slow tissue deformation within one scan. The ability to simultaneously characterize tissue motion and blood flow provides a useful approach to better understand cardiac dynamics during early developmental stages.

The combined use of surface acoustic wave (SAW) and phase-sensitive optical coherence tomography (PhS-OCT) is useful to evaluate the elasticity of layered biological tissues, such as normal skin. However, the pathological tissue is often originated locally, leading to the alternation of mechanical properties along both axial and lateral directions. We present a feasibility study on whether the SAW technique is sensitive to detect the alternation of mechanical property along the lateral direction within tissue, which is important for clinical utility of this technique to localize diseased tissue. Experiments are carried out on purposely designed tissue phantoms and ex vivo chicken breast samples, simulating the localized change of elasticity. A PhS-OCT system is employed not only to provide the ultra-high sensitive measurement of the generated surface waves on the tissue surface, but also to provide the real time imaging of the tissue to assist the elasticity evaluation of the heterogeneous tissue. The experimental results demonstrate that with PhS-OCT used as a pressure sensor, the SAW is highly sensitive to the elasticity change of the specimen in both vertical and lateral directions with a sensing depth of ∼5 mm with our current system setup, thus promising its useful clinical applications where the quantitative elasticity of localized skin diseases is needed to aid in diagnosis and treatment.

In this paper, we propose eigendecomposition- (ED-) based clutter filtering technique for 3D optical imaging of blood flow. Due to its best mean square approximation of the clutter, eigenregression filters can theoretically provide maximum clutter suppression. Compared to the existing clutter rejection techniques in the literature used for optical imaging of blood flow, ED-based clutter filtering is less sensitive to tissue motion and can efficiently suppress the clutter while preserving the flow information. Therefore, it creates images with better contrast in the presence of bulk motion. The performance of the proposed ED-based technique is compared with that of phase compensation method and static high-pass filtering. The quantitative and qualitative performances are compared with each other in phantom studies and in vivo imaging, respectively. Also, 3D image of microvascular structures in mouse ear is presented where the clutter has been suppressed with ED-based technique. This technique can be used in applications where involuntary movements due to cardiac and respiratory cycles are inevitable (such as retinal imaging).

We present a statistic method to measure the concentration of particles in flow by the use of optical coherence tomography (OCT). This method is based on the fact that the fluctuating numbers of particles contained within a small OCT detection volume caused by Brownian motion are governed by Poissonian distribution. Particle concentration is evaluated from the statistical analyzes of the OCT intensity signals that are backscattered by the moving particles. The method is experimentally verified with flow phantoms of polymer microspheres. Experimental results are in good agreement with the theoretical ones for low concentrations while relatively large discrepancies emerge for high concentrations., (© 2011 Optical Society of America)

We propose a Doppler optical micro-angiography (DOMAG) method to image flow velocities of the blood flowing in functional vessels within microcirculatory tissue beds in vivo. The method takes the advantages of recently developed optical micro-angiography (OMAG) technology, in which the endogenous optical signals backscattered from the moving blood cells are isolated from those originated from the tissue background, i.e., the tissue microstructures. The phase difference between adjacent A scans of OMAG flow signals is used to evaluate the flow velocity, similar to phase-resolved Doppler optical coherence tomography (PRDOCT). To meet the requirement of correlation between adjacent A scans in using the phase resolved technique to evaluate flow velocity, an ideal tissue-sample background (i.e., optically homogeneous tissue sample) is digitally reconstructed to replace the signals that represent the heterogeneous features of the static sample that are rejected in the OMAG flow images. Because of the ideal optical-homogeneous sample, DOMAG is free from the characteristic texture pattern noise due to the heterogeneous property of sample, leading to dramatic improvement of the imaging performance. A series of phantom flow experiments are performed to evaluate quantitatively the improved imaging performance. We then conduct in vivo experiments on a mouse brain to demonstrate that DOMAG is capable of quantifying the flow velocities within cerebrovascular network, down to capillary level resolution. Finally, we compare the in vivo imaging performance of DOMAG with that of PRDOCT, and show that DOMAG delivers at least 15-fold increase over the PRDOCT method in terms of the lower limit of flow velocity that can be detected.

Optical coherence tomography (OCT) is a non-contact, non-invasive and high-resolution imaging technique, suited to study early cardiovascular development. Alterations in hemodynamic conditions during early development are known to lead to cardiac defects, presumably as a result of changes in cardiac biomechanics produced by the alterations. In this paper, we demonstrate the use of a spectral domain OCT in visualizing and quantifying changes in cardiac wall motion and blood-flow velocities under normal and altered hemodynamic conditions in chicken embryos at an early stage of development (Hamburger-Hamilton stage HH18, approximately 3 days of incubation), focusing on the heart outflow tract (OFT). The OCT system employed acquired simultaneously microstructural and blood-flow images at a rate of 92 frames s(-1)with a spatial resolution of approximately 10 microm. OCT imaging allowed in vivo visualization of the OFT microstructures, e.g. the lumen, cardiac cushions and myocardium. We found that alterations in hemodynamic conditions, through OFT banding and vitelline-vein ligation, changed blood-flow velocities through the OFT, as expected. Further, OCT allowed quantification of changes in the dynamics of OFT wall motion. Our results therefore establish the utility of spectral domain OCT to study the influence of hemodynamic conditions on heart development in intact, in vivo chicken embryo models.

Tongue inspection (TI) is an important and unique diagnostic method in traditional Chinese medicine (TCM), because significant connections between various viscerae diseases and abnormalities in the tongue have been verified. In TCM, TI is simple and non invasive, but in clinical applications, TI is subjectively based on the experience and technique of physicians. To avoid this problem, optical coherence tomography (OCT) imaging is introduced here for TI. We study OCT imaging in rats in vivo from chronic gastritis group (model) and normal group (control) and quantitatively analyze the relative parameters, such as the thickness and the moisture degree of TI. Our results show that OCT images properly demonstrate the thickness of the tongue coating and the moisture degree of the tongue in both groups, and the thickness is increased in the model group from that in the normal group, while the moisture degree decreases. As a result, OCT technology has the potential to provide physicians with an objective diagnostic standard for visual TI in TCM clinical practice and research.

In describing the first-order properties of laser speckle under polarized illumination conditions, it is almost an article of faith that the contrast is unity. In many processing schemes, however, the contrast defined as the quotient of the standard deviation and the mean is calculated over a localized spatial region. In such cases, this local contrast displays a distribution of values that can depart substantially from unity. Properties of this distribution depend on details of the data acquisition and on the size of the local neighborhood over which the contrast is calculated. We demonstrate that this local contrast can be characterized in terms of a log-normal distribution. Further, we show that the two defining parameters of this model can in turn be expressed in terms of the minimum speckle size and the extent of the local neighborhood. Performance of the model is illustrated with some typical optical coherence tomography data.

The author describes a Fourier domain optical coherence tomography (FDOCT) system that is capable of full range complex imaging in vivo. This is achieved by introducing a constant carrier frequency into the OCT spectral interferograms at the time when imaging is performed. The complex functions of the spatial interferograms formed by each single wavelength are constructed before performing the Fourier transformation to localize the scatters within a sample. Two algorithms, based on Fourier filtering and Hilbert transformation, respectively, are described to achieve the full range complex FDOCT imaging. It is shown that the Hilbert transformation approach delivers better performance than the Fourier filtering method does in terms of tolerating the sample movement in vivo. The author finally demonstrates experimentally the system and algorithms for true in vivo imaging at a rate of 20,000 axial scans per second.

The transport properties of dense random media such as rutile powder layers and polyball suspensions are analyzed in visible and near infrared on the basis of experimental data on coherent backscattering, diffuse transmittance, and low-coherence interferometry. The developed technique of retrieval of the transport parameters of examined scattering media allows the evaluation of the transport mean free path l* and the effective refractive index n(ef) of the medium without a priori knowledge of the optical properties of the scattering particles. It is found that with decreasing wavelength lambda(0) the value of localization parameter 2pin(ef)l*/lambda(0) of the studied rutile samples abruptly drops and approaches approximately 2.6 at 473 nm. This peculiarity is caused by the very large scattering efficiency of scatterers in the vicinity of the first Mie resonance.

The rapid development in the field of optical coherence tomography has demanded increasingly sophisticated numerical models to enable the interpretation of image data and extract quantitative results. We use a matrix formulation of Fresnel's equations for multilayered media to extract layer-dependent thickness and refractive index directly from Fourier domain optical coherence tomography spectrograms. An eigenanalysis spectral decomposition approach is used to constrain the least squares fitting algorithm, avoiding the need for initial estimates of the parameter values. We demonstrate this novel quantitative analysis approach by using a multilayered phantom and show good agreement with the known layer parameter values. This approach introduces a powerful tool for the analysis of layer-dependent optical properties that could have an important role in the differentiation of healthy and diseased tissue.

A simple method is introduced to eliminate the autocorrelation artefacts in ultrafast spectral domain optical coherence tomography (SOCT) by use of the ensemble average of spectra within an individual B scan as the background signal, and then subtracting this from all the A scans within that B scan before performing the FFTs. This is updated continuously frame by frame. The method is tested on a volume-rate (C-mode) SOCT system to image the human fingertip in vivo with a volume rate at 8 s.

Low-level light-emitting imaging technique often detects the light emerged at the tissue surface that is generated internally from a specific target. However, in most cases, the high scattering nature of biological tissue limits the sensitivity and spatial resolution of this imaging modality. In this paper, we report that a significant improvement of chemiluminescence (CL) imaging performance in terms of both sensitivity and spatial resolution can be achieved by use of the topical application of glycerol solution onto tissue sample, i.e. optical clearing approach. Monte Carlo (MC) simulation of internally-launched point source shows that the decrease of scattering coefficient of turbid medium, which can be achieved by optical tissue clearing approach, causes stronger peak intensity with a narrower full-width at half-maximum (FWHM). The improvement becomes more significant with the source depth increasing from 1 to 5 mm. The experimental results shows that tissue clearing with 50% glycerol solution could largely improve the brightness and the spatial resolution of CL imaging when the target is covered by biological tissue with a thickness of either 1 or 3mm. This method could have potential applications for the in vivo low-level light imaging techniques.

An ideal diagnostic system for the human airways should be able to detect and define early development of premalignant pathological lesions, to facilitate optimal curative treatment and prevent irreversible and/or invasive lung disease. There is great need for exploration of safe, repeatable imaging techniques which can run at real-time and with high spatial resolution. In this study, optical coherence tomography (OCT) was utilized to acquire cross-sectional images of upper and lower airways using fresh pig lung resections as a model system. Obtained OCT images were compared with parallel tissue characterization by conventional histological analysis. Our objective was to determine whether OCT differentiates the composite structural layers and inherent anatomical variations along different airway locations. The data show that OCT can clearly display the multilayered structure of the airways. The subtle architectural differences in three separate anatomical locations including trachea, main bronchus and tertiary bronchus were clearly delineated. Images of the appropriate anatomical profiles, with depth of up to 2 mm and 10 microm spatial resolution were obtained by our current OCT system, which was sufficient for recognition of the epithelium, subepithelial tissues and cartilage. In addition, the relative thickness of individual structural components was accurately reflected and comparable to histological sections. These data support OCT as a highly feasible, optical biopsy tool, which merits further exploration for early diagnosis of human airway epithelial pathology.

The experimental methods of Doppler optical coherence tomography are applied for two-dimensional flow mapping of highly scattering fluid in flow with complex geometry. Converging flow (die entry) is used to demonstrate non-invasive methods to map varying velocity profiles before and after the entry. Complex geometry flow is scanned with approximately 10 x 10 x 10 microm3 spatial resolution. Structural images of the phantom and specific velocity images are demonstrated. A variety of velocity profiles have been obtained before and after the entry. Concave, blunted, parabolic and triangular profiles are obtained at different distances after the entry. Application of the technique to the study of blood circulation is discussed.