Vasculature Map Research Articles

Deep-Learning-Based Algorithm for the Removal of Electromagnetic Interference Noise in Photoacoustic Endoscopic Image Processing.

Despite all the expectations for photoacoustic endoscopy (PAE), there are still several technical issues that must be resolved before the technique can be successfully translated into clinics. Among these, electromagnetic interference (EMI) noise, in addition to the limited signal-to-noise ratio (SNR), have hindered the rapid development of related technologies. Unlike endoscopic ultrasound, in which the SNR can be increased by simply applying a higher pulsing voltage, there is a fundamental limitation in leveraging the SNR of PAE signals because they are mostly determined by the optical pulse energy applied, which must be within the safety limits. Moreover, a typical PAE hardware situation requires a wide separation between the ultrasonic sensor and the amplifier, meaning that it is not easy to build an ideal PAE system that would be unaffected by EMI noise. With the intention of expediting the progress of related research, in this study, we investigated the feasibility of deep-learning-based EMI noise removal involved in PAE image processing. In particular, we selected four fully convolutional neural network architectures, U-Net, Segnet, FCN-16s, and FCN-8s, and observed that a modified U-Net architecture outperformed the other architectures in the EMI noise removal. Classical filter methods were also compared to confirm the superiority of the deep-learning-based approach. Still, it was by the U-Net architecture that we were able to successfully produce a denoised 3D vasculature map that could even depict the mesh-like capillary networks distributed in the wall of a rat colorectum. As the development of a low-cost laser diode or LED-based photoacoustic tomography (PAT) system is now emerging as one of the important topics in PAT, we expect that the presented AI strategy for the removal of EMI noise could be broadly applicable to many areas of PAT, in which the ability to apply a hardware-based prevention method is limited and thus EMI noise appears more prominently due to poor SNR.

High Frame Rate Volumetric Imaging of Microbubbles Using a Sparse Array and Spatial Coherence Beamforming.

Volumetric ultrasound imaging of blood flow with microbubbles enables a more complete visualization of the microvasculature. Sparse arrays are ideal candidates to perform volumetric imaging at reduced manufacturing complexity and cable count. However, due to the small number of transducer elements, sparse arrays often come with high clutter levels, especially when wide beams are transmitted to increase the frame rate. In this study, we demonstrate with a prototype sparse array probe and a diverging wave transmission strategy, that a uniform transmission field can be achieved. With the implementation of a spatial coherence beamformer, the background clutter signal can be effectively suppressed, leading to a signal to background ratio improvement of 25 dB. With this approach, we demonstrate the volumetric visualization of single microbubbles in a tissue-mimicking phantom as well as vasculature mapping in a live chicken embryo chorioallantoic membrane.

Modified pixel level snake using bottom hat transformation for evolution of retinal vasculature map.

Small changes in retinal blood vessels may produce different pathological disorders which may further cause blindness. Therefore, accurate extraction of vasculature map of retinal fundus image has become a challenging task for analysis of different pathologies. The present study offers an unsupervised method for extraction of vasculature map from retinal fundus images. This paper presents the methodology for evolution of vessels using Modified Pixel Level Snake (MPLS) algorithm based on Black Top-Hat (BTH) transformation. In the proposed method, initially bimodal masking is used for extraction of the mask of the retinal fundus image. Then adaptive segmentation and global thresholding is applied on masked image to find the initial contour image. Finally, MPLS is used for evolution of contour in all four cardinal directions using external, internal and balloon potential. This proposed work is implemented using MATLAB software. DRIVE and STARE databases are used for checking the performance of the system. In the proposed work, various performance metrics such as sensitivity, specificity and accuracy are evaluated. The average sensitivity of 76.96%, average specificity of 98.34% and average accuracy of 96.30% is achieved for DRIVE database. This technique can also segment vessels of pathological images accurately; reaching the average sensitivity of 70.80%, average specificity of 96.40% and average accuracy of 94.41%. The present study provides a simple and accurate method for the detection of vasculature map for normal fundus images as well as pathological images. It can be helpful for the assessment of various retinal vascular attributes like length, diameter, width, tortuosity and branching angle.

Quantitative Handheld Swept-Source Optical Coherence Tomography Angiography in Awake Preterm and Full-Term Infants.

PurposeTo compare retinal vascular parameters acquired by handheld swept-source optical coherence tomography angiography (SS-OCTA) between nonsedated preterm and full-term infants.MethodsPreterm and full-term infants at the University of Washington Medical Center were enrolled. Retinal angiograms (nominal size ∼7 × 7 mm2) were obtained at each routine retinopathy of prematurity (ROP) screening session for preterms and once during the first 72 hours of life for full-terms. Macular vessel area density and nonperfusion area were evaluated on the binarized vasculature map in both small (1.5 × 1.5 mm) and large (3 × 3 mm) quadrants. Average vessel diameter and tortuosity values were obtained from each large vessel branch (length >200 µm). All vascular analyses used previously published algorithms.ResultsHandheld SS-OCTA captured 31 of 55 (56%) high-quality volumes on 8 awake preterm infants (gestational age 28 ± 4 weeks, birth weight 891 ± 314 g, postmenstrual age at first imaging session 37 ± 2 weeks) and 48 of 54 (89%) volumes on 12 awake full-term infants (gestational age 39 ± 1 weeks, birth weight 3405 ± 329 g). Signal-to-noise ratio was 5.08 ± 1.52 dB in preterm and 4.90 ± 1.12 dB in full-term infants. Preterm infants had higher mean large vessel tortuosity compared to full-term infants (P = 0.004). The large nasal quadrant vessel area density of infants with stage 3 and/or pre-plus or worse ROP was higher than other preterm infants (P = 0.007).ConclusionsAlthough inadequate image quality limited usable imaging sessions, handheld SS-OCTA achieved adequate signal-to-noise ratio in nonsedated infants for quantitative retinal vascular parameter analysis.Translational RelevanceLarge- and small-vessel parameters were associated with prematurity and ROP severity, respectively.

Detection of bifurcations and cross-over points from retinal vasculature map using modified window feature-point detection approach

Identification of feature points such as bifurcation points and cross-over points in retinal fundus images is useful for predicting the various cardiovascular diseases. In this paper, a new approach called the Modified Window Feature-point Detection (MWFD) is proposed to identify the vascular feature points in the fundus image. The MWFD technique makes use of two different windows 3×3 and 5×5 with alternative vessel pixel property for the detection of all feature points. This paper also resolves the problem of conversion of one cross-over point into two bifurcation points generated due to skeletonisation. The simulation is performed on the DRIVE database using MATLAB software. Simulation results show quantitative improvements in detection of feature points from retinal fundus image by increasing the number of true positives and reducing false positives and false negatives. These results provide an efficient and reliable technique for analysis of various retinal structures.

Detection of bifurcations and cross-over points from retinal vasculature map using modified window feature-point detection approach

Identification of feature points such as bifurcation points and cross-over points in retinal fundus images is useful for predicting the various cardiovascular diseases. In this paper, a new approach called the Modified Window Feature-point Detection (MWFD) is proposed to identify the vascular feature points in the fundus image. The MWFD technique makes use of two different windows 3×3 and 5×5 with alternative vessel pixel property for the detection of all feature points. This paper also resolves the problem of conversion of one cross-over point into two bifurcation points generated due to skeletonisation. The simulation is performed on the DRIVE database using MATLAB software. Simulation results show quantitative improvements in detection of feature points from retinal fundus image by increasing the number of true positives and reducing false positives and false negatives. These results provide an efficient and reliable technique for analysis of various retinal structures.

Optical-Resolution Photoacoustic Microscopy Using Transparent Ultrasound Transducer.

The opacity of conventional ultrasound transducers can impede the miniaturization and workflow of current photoacoustic systems. In particular, optical-resolution photoacoustic microscopy (OR-PAM) requires the coaxial alignment of optical illumination and acoustic-detection paths through complex beam combiners and a thick coupling medium. To overcome these hurdles, we developed a novel OR-PAM method on the basis of our recently reported transparent lithium niobate (LiNbO3) ultrasound transducer (Dangi et al., Optics Letters, 2019), which was centered at 13 MHz ultrasound frequency with 60% photoacoustic bandwidth. To test the feasibility of wearable OR-PAM, optical-only raster scanning of focused light through a transducer was performed while the transducer was fixed above the imaging subject. Imaging experiments on resolution targets and carbon fibers demonstrated a lateral resolution of 8.5 µm. Further, we demonstrated vasculature mapping using chicken embryos and melanoma depth profiling using tissue phantoms. In conclusion, the proposed OR-PAM system using a low-cost transparent LiNbO3 window transducer has a promising future in wearable and high-throughput imaging applications, e.g., integration with conventional optical microscopy to enable a multimodal microscopy platform capable of ultrasound stimulation.

Extraction of Vasculature Map of Color Retinal Fundus Image

This paper presents an unsupervised and novel method for extraction of vasculature map from colored retinal fundus images. Proposed technique makes use of a fusion of bimodal masking and global thresholding technique for extraction of vessels. For this, adaptive histogram equalization method is used for enhancement of the retinal input fundus images while, on the other hand, an average filter is used on the masked images to remove the noise from the image. At this stage, bimodal masking is used to generate the masked image to exclude the pixels that belong to the background. The use of this technique reduces the analysis time and computational effort as operations will be focused only on the object pixels. After that, a global thresholding technique is utilized on the masked foreground image, which produces a vasculature map with border. Since the border has no concern in our system, hence, it is removed using the mask generated through bimodal masking. Fundus images of DRIVE and STARE database is used to perform extensive computations. The results are encouraging as the proposed system shows better outcomes on 3-quality measures: average sensitivity, specificity, and accuracy which comes out to be (84.18%, 96.68% and 95.68%) and (81.79%, 90.74% and 90.08%) for DRIVE and STARE database respectively. The results prove that the proposed methodology is capable of extracting the vasculature map accurately, which can be further helpful for diagnosis, screening, and treatment of various disorders of fundus images.

Anatomically realistic simulation framework for ultrasound localization microscopy

Ultrasound Localization Microscopy (ULM) can map vessels at the capillary scale (<10 μm) by acquiring tens of thousands of images in which injected microbubbles are detected and tracked to generate super-resolved blood vessel maps. However, to our knowledge, there are no validation frameworks for ULM image formation algorithms. Herein, we developed a 3-D, anatomically realistic simulation tool based on serial two-photon microscopy (STPM). Rodent brain vasculature was segmented from STPM [1] into a graph-based model, which was then used to generate microbubble flow trajectories according to a velocity-diameter relationship derived from in vivo ULM data [2]. Ultrasound signals were obtained using a fast GPU-based simulator and reconstructed using our ULM image formation algorithm. We then proceeded to a parametric study. We first compared 2-D with 3-D imaging. Despite the latter's lower contrast, the gain in spatial information led to a more complete vasculature map. Localization precision was also enhanced since it was freed from the intrinsic localization error in the elevation direction. Also, increasing the number of transmits enhanced localization precision. From this study, we could establish a relationship between microbubble concentration and acquisition time for full network filling and optimal localization. This simulation tool provides thus a ground truth for the validation of ULM image formation algorithms and enables testing of new hypotheses. [1] R. Damseh et al., IEEE JBHI(2018). [2] V. Hingot et al., Sci Rep. (2019).

Fast and effective optic disk localization based on convolutional neural network

As a benchmark structure in the retina, the precise localization of the Optic Disc (OD) has received considerable attention from researchers owning to its importance for ophthalmic image analysis and retinopathy screening. In most literature works, although OD localization has achieved fairly good performance, rather less attention has been paid to supervised techniques. As the ODs are common in characteristics and form a fixed pattern, we propose in this paper an OD localization method based on Convolutional Neural Networks (CNNs). In data preparation, the blue channel in the fundus image, which is always empty or noisy and tends to be uninformative, is replaced by coarsely segmented vasculature maps (Red channel, Green channel and vasculatures are denoted as RGV). In addition, the input of the CNN structures is rectangular instead of square in order to involve more context information of the vasculatures. For training, a two-stage process is designed to alleviate the class-imbalance problem by choosing large number of positive samples at the first stage and choosing samples at the center of OD to fine-tune the fist-stage model at the second stage. Then a probability guided search algorithm is developed to improve the efficiency of OD localization by selectively searching patches with large chances to be an OD and their neighbors. Finally, the precise OD position is located as center of the highest probability regions after weighted voting. Extensive experiments on four publicly available databases demonstrate the effectiveness and efficiency of the proposed method, with an average detection rate of 99.11% and detection time less than 15 s per image.

A generalized method for the detection of vascular structure in pathological retinal images

Variations in blood vasculature morphology of retinal fundus images is one of the dominant characteristic for the early detection and analysis of retinal abnormalities. Therefore the accurate interpretation of blood vasculature is useful for ophthalmologists to diagnose patients that suffer from retinal abnormalities. A generalized method to detect and segment blood vasculature using retinal fundus images has been proposed in this work using (i) preprocessing for quality improvement of retinal fundus images, (ii) initial segmentation of vasculature map to find vascular and non vascular structures, (iii) extraction of relevant set of geometrical based features from the vasculature map and intensity based features from original retinal fundus image that differentiate vascular and non vascular structures efficiently, (iv) supervised classification of vascular and non vascular structures using the extracted features, and (v) joining of candidate vascular structures to create connectivity. The proposed method is evaluated on clinically acquired dataset and different publically available standard datasets such as DRIVE, STARE, ARIA and HRF. The clinically acquired dataset consists of 468 retinal fundus images comprising of healthy images, images with mild, intermediate and severe pathologies. Test results of the proposed method shows average sensitivity/specificity/accuracy of 85.43/97.94/95.45 on the 785 retinal fundus images. The proposed method shows an improvement of 14.01% in sensitivity without degrading specificity and accuracy in comparison to the recently published methods.

In Vivo Identification of the Posttrabecular Aqueous Outflow Pathway Using Swept-Source Optical Coherence Tomography.

The purpose of this study was to investigate a novel imaging technique to identify the continuous posttrabecular aqueous outflow pathway from a single B-scan, using swept-source optical coherence tomography (SS-OCT). Three-dimensional volume scans of the temporal or nasal side of the anterior segment area at the limbus were acquired from 11 eyes of 11 healthy subjects, using SS-OCT. The aqueous outflow pathway was identified using an en face OCT image and reconstructed images of the vasculature (vasculature map). Delineation of the whole aqueous outflow pathway in a single B-scan was accomplished by reslicing the volume scan. The posttrabecular aqueous outflow pathway was successfully identified in 10 eyes (90.9%). Combined with a flattening technique, the en face video and vasculature map showed a clear blood stream that could not be observed on a sequential stack of B-scans. In the en face images, the vessels were widely branched in the episclera venous plexus, perpendicularly penetrating the scleral stroma. Vessels running parallel to Schlemm's canal and the collector channels were observed in the deeper region of the sclera. The average longitudinal diameter of the vessel was 29.7 ± 6.6 μm at the episcleral venous plexus, and it was significantly larger than that in the deep scleral aqueous plexus (22.0 ± 4.8 μm; P = 0.0002). The continuous posttrabecular aqueous outflow pathway could be identified from a single B-scan and quantitatively analyzed using SS-OCT with en face imaging and volume scan reslicing.

Self-contained image mapping of placental vasculature in 3D ultrasound-guided fetoscopy.

Surgical navigation technology directed at fetoscopic procedures is relatively underdeveloped compared with other forms of endoscopy. The narrow fetoscopic field of views and the vast vascular network on the placenta make examination and photocoagulation treatment of twin-to-twin transfusion syndrome challenging. Though ultrasonography is used for intraoperative guidance, its navigational ability is not fully exploited. This work aims to integrate 3D ultrasound imaging and endoscopic vision seamlessly for placental vasculature mapping through a self-contained framework without external navigational devices. This is achieved through development, integration, and experimentation of novel navigational modules. Firstly, a framework design that addresses the current limitations based on identified gaps is conceptualized. Secondly, integration of navigational modules including (1) ultrasound-based localization, (2) image alignment, and (3) vision-based tracking to update the scene texture map is implemented. This updated texture map is projected to an ultrasound-constructed 3D model for photorealistic texturing of the 3D scene creating a panoramic view of the moving fetoscope. In addition, a collaborative scheme for the integration of the modular workflow system is proposed to schedule updates in a systematic fashion. Finally, experiments are carried out to evaluate each modular variation and an integrated collaborative scheme of the framework. The modules and the collaborative scheme are evaluated through a series of phantom experiments with controlled trajectories for repeatability. The collaborative framework demonstrated the best accuracy (5.2% RMS error) compared with all the three single-module variations during the experiment. Validation on an ex vivo monkey placenta shows visual continuity of the freehand fetoscopic panorama. The proposed developed collaborative framework and the evaluation study of the framework variations provide analytical insights for effective integration of ultrasonography and endoscopy. This contributes to the development of navigation techniques in fetoscopic procedures and can potentially be extended to other applications in intraoperative imaging.

Liquid metal angiography for mega contrast X-ray visualization of vascular network in reconstructing in-vitro organ anatomy.

Visualization on the anatomical vessel networks plays a vital role in the physiological or pathological investigations. However, so far it still remains a big challenge to identify the fine structures of the smallest capillary vessel networks via conventional imaging ways. Here, the room temperature liquid metal angiography was proposed for the first time to generate mega contrast X-ray images for multiscale vasculature mapping. Particularly, gallium was adopted as the room temperature liquid metal contrast agent and infused into the vessels of in vitro pig hearts and kidneys. We scanned the samples under X-ray and compared the angiograms with those obtained via conventional contrast agent--the iohexol. As quantitatively demonstrated by the grayscale histograms and numerical indexes, the contrast of the vessels to the surrounding tissues in the liquid metal angiograms is orders higher than that of the iohexol enhanced images. And the angiogram has reached detailed enough width of 0.1 mm for the tiny vessels, which indicated that the capillaries can be clearly distinguished under the liquid metal enhanced images. Further, with tomography from the micro-CT, we also managed to reconstruct the 3-D structures of the kidney vessels. Tremendous clarity and efficiency of the method over existing approaches have been experimentally clarified. It was disclosed that the usually invisible capillary networks now become distinctively clear in the gallium angiograms. This basic mechanism has generalized purpose and can be extended to a wide spectrum of 3-D computational tomographic areas. It opens a new soft tool for quickly reconstructing high-resolution spatial channel networks for scientific researches as well as engineering practices where complicated and time-consuming resections are no longer a necessity.

Phase-Variance Optical Coherence Tomography: A Technique for Noninvasive Angiography

Phase-variance optical coherence tomography (PV-OCT) provides volumetric imaging of the retinal vasculature without the need for intravenous injection of a fluorophore. We compare images from PV-OCT and fluorescein angiography (FA) for normal individuals and patients with age-related macular degeneration (AMD) and diabetic retinopathy.This is an evaluation of a diagnostic technology.Four patients underwent comparative retinovascular imaging using FA and PV-OCT. Imaging was performed on 1 normal individual, 1 patient with dry AMD, 1 patient with exudative AMD, and 1 patient with nonproliferative diabetic retinopathy.Fluorescein angiography imaging was performed using a Topcon Corp (Tokyo, Japan) (TRC-50IX) camera with a resolution of 1280 (H) × 1024 (V) pixels. The PV-OCT images were generated by software data processing of the entire cross-sectional image from consecutively acquired B-scans. Bulk axial motion was calculated and corrected for each transverse location, reducing the phase noise introduced from eye motion. Phase variance was calculated through the variance of the motion-corrected phase changes acquired within multiple B-scans at the same position. Repeating these calculations over the entire volumetric scan produced a 3-dimensional PV-OCT representation of the vasculature.Feasibility of rendering retinal and choroidal microvasculature using PV-OCT was compared qualitatively with FA, the current gold standard for retinovascular imaging.Phase-variance OCT noninvasively rendered a 2-dimensional depth color-coded vasculature map of the retinal and choroidal vasculature. The choriocapillaris was imaged with better resolution of microvascular detail using PV-OCT. Areas of geographic atrophy and choroidal neovascularization imaged by FA were depicted by PV-OCT. Regions of capillary nonperfusion from diabetic retinopathy were shown by both imaging techniques; there was not complete correspondence between microaneurysms shown on FA and PV-OCT images.Phase-variance OCT yields high-resolution imaging of the retinal and choroidal microvasculature that compares favorably with FA.

Mesenteric Vasculature-Guided Small Bowel Segmentation on 3-D CT

Due to its importance and possible applications in visualization, tumor detection and preoperative planning, automatic small bowel segmentation is essential for computer-aided diagnosis of small bowel pathology. However, segmenting the small bowel directly on computed tomography (CT) scans is very difficult because of the low image contrast on CT scans and high tortuosity of the small bowel and its close proximity to other abdominal organs. Motivated by the intensity characteristics of abdominal CT images, the anatomic relationship between the mesenteric vasculature and the small bowel, and potential usefulness of the mesenteric vasculature for establishing the path of the small bowel, we propose a novel mesenteric vasculature map-guided method for small bowel segmentation on high-resolution CT angiography scans. The major mesenteric arteries are first segmented using a vessel tracing method based on multi-linear subspace vessel model and Bayesian inference. Second, multi-view, multi-scale vesselness enhancement filters are used to segment small vessels, and vessels directly or indirectly connecting to the superior mesenteric artery are classified as mesenteric vessels. Third, a mesenteric vasculature map is built by linking vessel bifurcation points, and the small bowel is segmented by employing the mesenteric vessel map and fuzzy connectness. The method was evaluated on 11 abdominal CT scans of patients suspected of having carcinoid tumors with manually labeled reference standard. The result, 82.5% volume overlap accuracy compared with the reference standard, shows it is feasible to segment the small bowel on CT scans using the mesenteric vasculature as a roadmap.

A comparison of Doppler optical coherence tomography methods

: We compare, in detail, the phase-resolved color Doppler (PRCD), phase-resolved Doppler variance (PRDV) and intensity-based Doppler variance (IBDV) methods. All the methods are able to quantify flow speed when the flow rate is within a certain range, which is dependent on the adjacent A-line time interval. While PRCD is most sensitive when the flow direction is along the probing beam, PRDV and IBDV can be used to measure the flow when the flow direction is near perpendicular to the probing beam. However, the values of PRDV and IBDV are Doppler angle-dependent when the Doppler angle is above a certain threshold. The sensitivity of all the methods can be improved by increasing the adjacent A-line time interval while still maintaining a high sampling density level. We also demonstrate for the first time, to the best of our knowledge, high resolution inter-frame PRDV method. In applications where mapping vascular network such as angiogram is more important than flow velocity quantification, IBDV and PRDV images show better contrast than PRCD images. The IBDV and PRDV show very similar characteristics and demonstrate comparable results for vasculature mapping. However, the IBDV is less sensitive to bulk motion and with less post-processing steps, which is preferred for fast data processing situations. In vivo imaging of mouse brain with intact skull and human skin with the three methods were demonstrated and the results were compared. The IBDV method was found to be able to obtain high resolution image with a relative simple processing procedure.

Foveal Avascular Zone and Its Relationship to Foveal Pit Shape

To investigate the retinal microvasculature at the fovea and peripheral retina in humans using an adaptive optics scanning laser ophthalmoscope (AOSLO) and to examine the association of foveal avascular zone (FAZ) and foveal pit morphology. Retinal imaging of the foveal capillary network was performed on 11 subjects (15 eyes; age range 20 to 54 years) with an AOSLO. Standard deviation maps of the AOSLO images were generated from ∼10 to 30 frames, producing high-resolution maps delineating the complete capillary distribution of the retina. Foveal pit morphology was investigated in the same subjects by using a spectral domain optical coherence tomography. In an additional subject, only a relatively large retinal vasculature map was obtained using AOSLO. A well-demarcated FAZ was seen in 11 subjects tested with foveal capillary imaging. There was considerable individual variation in the size and shape of the FAZ. The mean FAZ area and mean FAZ effective diameter were 0.33 mm(2) and 622 μm, respectively. Foveal thickness was found to be negatively correlated with the FAZ effective diameter. The structure of the capillary network could be evaluated in the fovea and parafovea using our approach. We find that a smaller FAZ is associated with a narrower foveal pit opening and a thicker fovea.

Imaging limbal and scleral vasculature using Swept Source Optical Coherence Tomography.

We demonstrate an application of high-speed swept source optical coherence tomography for vessel visualization in the anterior segment of the human eye. The human corneo-scleral junction and sclera was imaged in vivo. Imaging was performed using a swept source OCT system operating at the 1050nm wavelength range and 100kHz A-scan rate. High imaging speed enables the generation of 3D depth-resolved vasculature maps. The vessel visualization method revealed a rich vascular system in the conjunctiva and episclera.

Variable velocity range imaging of the choroid with dual-beam optical coherence angiography

In this study, we present dual-beam Doppler optical coherence angiography with variable beam separation. Altering beam distance, independently of the scanning protocol, provides a flexible way to select the velocity range of detectable blood flow. This system utilized a one-micrometer wavelength light source to visualize deep into the posterior eye, i.e., the choroid. Two-dimensional choroidal vasculature maps of a human subject acquired with different beam separations, and hence with several velocity ranges, are presented. Combining these maps yields a semi-quantitative visualization of axial velocity of the choroidal circulation. The proposed technique may be useful for identifying choroidal abnormalities that occur in pathological conditions of the eye.