Acner Camino

Oregon Health & Science University

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Yali Jia

Oregon Health & Science University

David Huang

New York University

Jie Wang

Tianjin Medical University

Yukun Guo

Oregon Health & Science University

Thomas S. Hwang

Oregon Health & Science University

Xiang Wei

Hansoh Pharma (China)

Shaohua Pi

University of Pittsburgh

William O. Cepurna

Oregon Health & Science University

John C. Morrison

Johns Hopkins University

Steven T. Bailey

Oregon Health & Science University

Cooperative Institutions

Oregon Health & Science University

Shandong Normal University

Changchun University of Science and Technology

Simon Fraser University

Universidad de Salamanca

Universitat Jaume I

Research to Prevent Blindness

Chinese Academy of Sciences

Ophthalmology Associates (United States)

Prevent Blindness

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DETECTION OF CLINICALLY UNSUSPECTED RETINAL NEOVASCULARIZATION WITH WIDE-FIELD OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY

Retina (2019)

Qi Sheng You Yukun Guo Jie Wang Xiang Wei Acner Camino

To evaluate wide-field optical coherence tomography angiography (OCTA) for detection of clinically unsuspected neovascularization (NV) in diabetic retinopathy (DR).This prospective observational single-center study included adult patients with a clinical diagnosis of nonproliferative DR. Participants underwent a clinical examination, standard 7-field color photography, and OCTA with commercial and prototype swept-source devices. The wide-field OCTA was achieved by montaging five 6 × 10-mm scans from a prototype device into a 25 × 10-mm image and three 6 × 6-mm scans from a commercial device into a 15 × 6-mm image. A masked grader determined the retinopathy severity from color photographs. Two trained readers examined conventional and wide-field OCTA images for the presence of NV.Of 27 participants, photographic grading found 13 mild, 7 moderate, and 7 severe nonproliferative DR. Conventional 6 × 6-mm OCTA detected NV in 2 eyes (7%) and none with 3 × 3-mm scans. Both prototype and commercial wide-field OCTA detected NV in two additional eyes. The mean area of NV was 0.38 mm (range 0.17-0.54 mm). All eyes with OCTA-detected NV were photographically graded as severe nonproliferative DR.Wide-field OCTA can detect small NV not seen on clinical examination or color photographs and may improve the clinical evaluation of DR.

Grading (engineering)

10.1097/iae.0000000000002487

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Citations (53)

Automated drusen detection in dry age-related macular degeneration by multiple-depth, en face optical coherence tomography

Biomedical Optics Express (2017)

Rui Zhao Acner Camino Jie Wang Ahmed M. Hagag Yansha Lu

We introduce a method to automatically detect drusen in dry age-related macular degeneration (AMD) from optical coherence tomography with minimum need for layer segmentation.The method is based on the en face detection of drusen areas in C-scans at certain distances above the Bruch's membrane, circumventing the difficult task of pathologic retinal pigment epithelium segmentation.All types of drusen can be detected, including the challenging subretinal drusenoid deposits (pseudodrusen).The high sensitivity and accuracy demonstrated here shows its potential for detection of drusen onset in early AMD.

Drusen

10.1364/boe.8.005049

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Citations (24)

Development and validation of a deep learning algorithm for distinguishing the nonperfusion area from signal reduction artifacts on OCT angiography

Biomedical Optics Express (2019)

Yukun Guo Tristan T. Hormel Honglian Xiong Bingjie Wang Acner Camino

The capillary nonperfusion area (NPA) is a key quantifiable biomarker in the evaluation of diabetic retinopathy (DR) using optical coherence tomography angiography (OCTA).However, signal reduction artifacts caused by vitreous floaters, pupil vignetting, or defocus present significant obstacles to accurate quantification.We have developed a convolutional neural network, MEDnet-V2, to distinguish NPA from signal reduction artifacts in 6×6 mm 2 OCTA.The network achieves strong specificity and sensitivity for NPA detection across a wide range of DR severity and scan quality.

SIGNAL (programming language)

10.1364/boe.10.003257

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Citations (53)

Real-time cross-sectional and en face OCT Angiography in Graphics Processing Unit

Investigative Ophthalmology & Visual Science (2018)

Xiang Wei Acner Camino Shaohua Pi William O. Cepurna David Huang

Graphics processing unit

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Regression-based algorithm for bulk motion subtraction in optical coherence tomography angiography

Biomedical Optics Express (2017)

Acner Camino Yali Jia Gangjun Liu Jie Wang David Huang

We developed an algorithm to remove decorrelation noise due to bulk motion in optical coherence tomography angiography (OCTA) of the posterior eye. In this algorithm, OCTA B-frames were divided into segments within which the bulk motion velocity could be assumed to be constant. This velocity was recovered using linear regression of decorrelation versus the logarithm of reflectance in axial lines (A-lines) identified as bulk tissue by percentile analysis. The fitting parameters were used to calculate a reflectance-adjusted upper bound threshold for bulk motion decorrelation. Below this threshold, voxels are identified as non-flow tissue, their flow values are set to zeros. Above this threshold, the voxels are identified as flow voxels and bulk motion velocity is subtracted from each using a nonlinear decorrelation-velocity relationship previously established in laboratory flow phantoms. Compared to the simpler median-subtraction method, the regression-based bulk motion subtraction improved angiogram signal-to-noise ratio, contrast, vessel density repeatability, and bulk motion noise cleanup in the foveal avascular zone, while preserving the connectivity of the vascular networks in the angiogram.

Decorrelation

Subtraction

10.1364/boe.8.003053

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Citations (40)

Effect of ambient pressure on femtosecond laser-induced breakdown spectroscopy of Al in argon

International Conference on Optoelectronics and Microelectronics (2012)

Agnes Nakimana Haiyan Tao Acner Camino Xun Gao Zuoqiang Hao

The effects of ambient pressures on the intensity of spectral emission, electron temperature and density of femtosecond laser produced plasma have been investigated. For this purpose, Al targets were ablated by employing a Ti: Sapphire laser system (50fs, 800nm) under various filling pressures of argon gas. The optical emission spectroscopy of Al plasma has been studied using the Laser Induced Breakdown Spectroscopy (LIBS) system. The results indicate that the pressure of the ambient atmosphere is one of the controlling factors of the plasma plume characteristics. The measurements reveal also that some lines which are nearly unresolved at high pressures become well resolved at low pressures.

Laser-induced breakdown spectroscopy

Ambient pressure

10.1109/icoom.2012.6316238

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Monitoring Retinal Responses to Acute Intraocular Pressure Elevation in Rats with Visible Light Optical Coherence Tomography

Investigative Ophthalmology & Visual Science (2019)

Shaohua Pi Tristan T. Hormel Xiang Wei William O. Cepurna Acner Camino

Elevated intraocular pressure (IOP) is an important risk factor for glaucoma. However, the role of IOP in glaucoma progression, as well as retinal physiology in general, remains incompletely understood. We demonstrate the use of visible light optical coherence tomography to measure retinal responses to acute IOP elevation in Brown Norway rats. We monitored retinal responses in reflectivity, angiography, blood flow, oxygen saturation (sO2), and oxygen metabolism over a range of IOP from 10 to 100 mmHg. As IOP was elevated, nerve fiber layer reflectivity was found to decrease. Vascular perfusion in the three retinal capillary plexuses remained steady until IOP exceeded 70 mmHg and arterial flow was noted to reverse periodically at high IOPs. However, a significant drop in total retinal blood flow was observed first at 40 mmHg. As IOP increased, the venous sO2 demonstrated a gradual decrease despite steady arterial sO2, which is consistent with increased arterial-venous oxygen extraction across the retinal capillary beds. Calculated total retinal oxygen metabolism was steady, reflecting balanced responses of blood flow and oxygen extraction, until IOP exceeded 40 mmHg, and fell to 0 at 70 and 80 mmHg. Above this, measurements were unattainable. All measurements reverted to baseline when the IOP was returned to 10 mmHg, indicating good recovery following acute pressure challenge. These results demonstrate the ability of this system to monitor retinal oxygen metabolism noninvasively and how it can help us understand retinal responses to elevated IOP.

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Automatic quantification of choroidal neovascularization lesion area on OCT angiography based on density cell-like P systems with active membranes

Biomedical Optics Express (2018)

Jie Xue Acner Camino Steven T. Bailey Xiyu Liu Dengwang Li

Detecting and quantifying the size of choroidal neovascularization (CNV) is important for the diagnosis and assessment of neovascular age-related macular degeneration. Depth-resolved imaging of the retinal and choroidal vasculature by optical coherence tomography angiography (OCTA) has enabled the visualization of CNV. However, due to the prevalence of artifacts, it is difficult to segment and quantify the CNV lesion area automatically. We have previously described a saliency algorithm for CNV detection that could identify a CNV lesion area with 83% accuracy. However, this method works under the assumption that the CNV region is the most salient area for visual attention in the whole image and consequently, errors occur when this requirement is not met (e.g. when the lesion occupies a large portion of the image). Moreover, saliency image processing methods cannot extract the edges of the salient object very accurately. In this paper, we propose a novel and automatic CNV segmentation method based on an unsupervised and parallel machine learning technique named density cell-like P systems (DEC P systems). DEC P systems integrate the idea of a modified clustering algorithm into cell-like P systems. This method improved the accuracy of detection to 87.2% on 22 subjects and obtained clear boundaries of the CNV lesions.

10.1364/boe.9.003208

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Citations (25)

Three Dimensional Evaluation of Foveal Ischemia in Diabetic Retinopathy

Investigative Ophthalmology & Visual Science (2019)

Bingjie Wang Acner Camino Shaohua Pi Yukun Guo David Huang

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Real-time retinal layer segmentation of OCT volumes with GPU accelerated inferencing using a compressed, low-latency neural network

Biomedical Optics Express (2020)

Svetlana Borkovkina Acner Camino Worawee Janpongsri Marinko V. Šarunic Yifan Jian

Segmentation of retinal layers in optical coherence tomography (OCT) is an essential step in OCT image analysis for screening, diagnosis, and assessment of retinal disease progression. Real-time segmentation together with high-speed OCT volume acquisition allows rendering of en face OCT of arbitrary retinal layers, which can be used to increase the yield rate of high-quality scans, provide real-time feedback during image-guided surgeries, and compensate aberrations in adaptive optics (AO) OCT without using wavefront sensors. We demonstrate here unprecedented real-time OCT segmentation of eight retinal layer boundaries achieved by 3 levels of optimization: 1) a modified, low complexity, neural network structure, 2) an innovative scheme of neural network compression with TensorRT, and 3) specialized GPU hardware to accelerate computation. Inferencing with the compressed network U-NetRT took 3.5 ms, improving by 21 times the speed of conventional U-Net inference without reducing the accuracy. The latency of the entire pipeline from data acquisition to inferencing was only 41 ms, enabled by parallelized batch processing. The system and method allow real-time updating of en face OCT and OCTA visualizations of arbitrary retinal layers and plexuses in continuous mode scanning. To the best our knowledge, our work is the first demonstration of an ophthalmic imager with embedded artificial intelligence (AI) providing real-time feedback.

10.1364/boe.395279

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Citations (45)