3D Retinal Vessel Density Mapping With OCT-Angiography

Sarabi, Mona Sharifi; Khansari, Maziyar M.; Zhang, Jiong; Kushner-Lenhoff, Sam; Gahm, Jin Kyu; Qiao, Yuchuan; Kashani, Amir H; Shi, Yonggang

doi:10.1109/jbhi.2020.3023308

Cited by 15 publications

(11 citation statements)

References 62 publications

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“…Finally, in the literature, there are reports assessing the impact of the 3D representation of macula blood vessels [25][26][27][28][29][30][49][50][51][52]. These methods were based on surface and volumetric rendering [25, 28-30, 49, 50, 52] of the original 3D OCTA volume or they interpolated the 3D representation from 2D OCTA B-scans [26,27,51].…”

Section: Discussionmentioning

confidence: 99%

“…These methods were based on surface and volumetric rendering [25, 28-30, 49, 50, 52] of the original 3D OCTA volume or they interpolated the 3D representation from 2D OCTA B-scans [26,27,51]. They succeeded in generating a 3D depiction of the macula's volume [25][26][27][49][50][51], or they developed methods to generate a 3D shape model [28], map [29,52], and surfacing the macula vasculature [30]. Similar to the OCTA quantitative metrics discussion in the preceding paragraph, the aim was to assess the integrity or the disruption of the macula blood vessels.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, other researchers investigated the use of 3D volumetric assessment to generate a 3D volume of specified macula's zones (e.g. Fovea Plana) [25], 3D presentation of the entire macula's vessels [26,27,[49][50][51], 3D shape modeling of the macula's microvasculature [28,52], or 3D metrics of the macula's vessel density [29] and surface [30]. However, considering the 3D shape of the macula, displaying sequential OCTA frames within each macula's layers, and improving the display of vessels at deep regions (i.e.…”

Section: Introductionmentioning

confidence: 99%

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Reconstruction and Visualization of 5μm Sectional Coronal Views for Macula Vasculature in OptoVue OCTA

et al. 2023

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A Computerized Medical Image Processing (CMIP) method is proposed to address the current challenges of optical coherence tomography angiography (OCTA): (1) the need for observing the macula vasculature concerning natural curvature of the macula region; (2) the need for generating OCTA frames at successive small depths in all macula layers; and (3) the need for enhancing the visibility of blood vessels, particularly below the outer retina region. The proposed CMIP method involves image preprocessing, reconstruction, and enhancement stages. Twenty subjects were obtained from the OCTA500 dataset, which was obtained from the OptoVue OCTA machine. The 20 subjects comprise the two OCTA fields of view (FOV), right and left eyes (OD and OS), and five common macula disorders. The sequential enface OCTA images at 5µm macula depths were displayed. The presentation of the macula vasculature was enhanced at all depths. The resulting new ophthalmic views enable: (1) avoiding the superimposition of macula vasculature into a projection map; (2) enhancing the OCTA presentation of blood vessels; and (3) inspecting the macula's 3D oval-shaped. The proposed CMIP method can generate sectional macula coronal views (MCV) for every 5µm depth, clarifying the macula's curvature in a way that has not been presented in OCTA machines. Therefore, "tracking" the 3D propagation of the blood vessel network at all macula depths becomes possible. Furthermore, the blood vessels' display at all macula depths, including the deep choroid layers, is enhanced. The method yields futuristic ophthalmic advantages that would allow the physician to precisely inspect the 3D localization and diffusion of the macula disorders. The method is invariant to the OCTA's FOVs, macula disorder, and OD or OS eye.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reconstruction and Visualization of 5μm Sectional Coronal Views for Macula Vasculature in OptoVue OCTA

et al. 2023

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“…This study was inspired by our previous work (Sarabi et al, 2020), where we developed a 3D retinal vessel density mapping approach for optical coherence tomography angiography (OCTA) and demonstrated its efficacy in localized detection of microvascular changes and monitoring retinal disease progression in different clinical applications such as normal aging and diabetic retinopathy (DR). Despite some similarities between the two studies, with respect to two-module framework design for fine-scale vessel segmentation and non-linear registration, there are still some fundamental differences in the method development.…”

Section: Discussionmentioning

confidence: 99%

Vessel Density Mapping of Cerebral Small Vessels on 3D High Resolution Black Blood MRI

Sarabi

Jann

et al. 2023

Preprint

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Cerebral small vessels are largely inaccessible to existing clinical in vivo imaging technologies. This study aims to present a novel analysis pipeline for vessel density mapping of cerebral small vessels from high-resolution 3D black-blood MRI at 3T. Twenty-eight subjects (10 under 35 years old, 18 over 60 years old) were imaged with the T1-weighted turbo spin-echo with variable flip angles (T1w TSE-VFA) sequence optimized for black-blood small vessel imaging with iso-0.5mm spatial resolution at 3T. Hessian-based vessel segmentation methods (Jerman, Frangi and Sato filter) were evaluated by vessel landmarks and manual annotation of lenticulostriate arteries (LSAs). Using optimized vessel segmentation, large vessel pruning and non-linear registration, a semiautomatic pipeline was proposed for quantification of small vessel density across brain regions and further for localized detection of small vessel changes across populations. Voxel-level statistics was performed to compare vessel density between two age groups. Additionally, local vessel density of aged subjects was correlated with their corresponding gross cognitive and executive function (EF) scores using Montreal Cognitive Assessment (MoCA) and EF composite scores compiled with Item Response Theory (IRT). Jerman filter showed better performance for vessel segmentation than Frangi and Sato filter which was employed in our pipeline. Cerebral small vessels on the order of a few hundred microns can be delineated using the proposed analysis pipeline on 3D black-blood MRI at 3T. The mean vessel density across brain regions was significantly higher in young subjects compared to aged subjects. In the aged subjects, localized vessel density was positively correlated with MoCA and IRT EF scores. The proposed pipeline is able to segment, quantify, and detect localized differences in vessel density of cerebral small vessels based on 3D high-resolution black-blood MRI. This framework may serve as a tool for localized detection of small vessel density changes in normal aging and cerebral small vessel disease.

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“…1 (b)), and the 3D spatial information of the vessels are not utilized. 3D analysis and visualization of blood vessels can provide additional spatial information that is not available in 2D images, and are very useful for observing vascular changes [10,11,12]. Zhang et al [3] built a 3D microvascular shape modeling framework based on the original volume of OCTA.…”

Section: Introductionmentioning

confidence: 99%

Cross-Domain Depth Estimation Network for 3D Vessel Reconstruction in OCT Angiography

Liu

Zhang

et al. 2021

Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

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Optical Coherence Tomography Angiography (OCTA) has been widely used by ophthalmologists for decision-making due to its superiority in providing caplillary details. Many of the OCTA imaging devices used in clinic provide high-quality 2D en face representations, while their 3D data quality are largely limited by low signal-to-noise ratio and strong projection artifacts, which restrict the performance of depthresolved 3D analysis. In this paper, we propose a novel 2D-to-3D vessel reconstruction framework based on the 2D en face OCTA images. This framework takes advantage of the detailed 2D OCTA depth map for prediction and thus does not rely on any 3D volumetric data. Based on the data with available vessel depth labels, we first introduce a network with structure constraint blocks to predict the depth of blood vessels in other cross-domain en face OCTA data with unavailable labels. Afterwards, a depth adversarial adaptation module is proposed for better unsupervised cross-domain training, since images captured using different devices may suffer from varying image contrast and noise levels. Finally, vessels are reconstructed in 3D space by utilizing the estimated depth map and 2D vascular information. Experimental results demonstrate the effectiveness of our method and its potential to guide subsequent vascular analysis in 3D domain.

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3D Retinal Vessel Density Mapping With OCT-Angiography

Cited by 15 publications

References 62 publications

Reconstruction and Visualization of 5μm Sectional Coronal Views for Macula Vasculature in OptoVue OCTA

Reconstruction and Visualization of 5μm Sectional Coronal Views for Macula Vasculature in OptoVue OCTA

Vessel Density Mapping of Cerebral Small Vessels on 3D High Resolution Black Blood MRI

Cross-Domain Depth Estimation Network for 3D Vessel Reconstruction in OCT Angiography

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