1. Marinko V. Sarunic

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    1. Mentioned In 78 Articles

    2. Quantitative multi-contrast in vivo mouse imaging with polarization diversity optical coherence tomography and angiography

      Explore OSA | OSA Publishing Ophthalmology
      Quantitative multi-contrast in vivo mouse imaging with polarization diversity optical coherence tomography and angiography
      Retinal microvasculature and the retinal pigment epithelium (RPE) play vital roles in maintaining the health and metabolic activity of the eye. Visualization of these retina structures is essential for pre-clinical studies of vision-robbing diseases, such as age-related macular degeneration (AMD). We have developed a quantitative multi-contrast polarization diversity OCT and angiography (QMC-PD-OCTA) system for imaging and visualizing pigment in the RPE using degree of polarization uniformity (DOPU), along with flow ...
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      Mentions: Shuichi Makita Yoshiaki Yasuno University of British Columbia

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

      Explore OSA | OSA Publishing
      Real-time retinal layer segmentation of OCT volumes with GPU accelerated inferencing using a compressed, low-latency neural network
      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 ...
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      Mentions: Oregon Health & Science University Marinko V. Sarunic Simon Fraser University

    4. Ensemble Deep Learning for Diabetic Retinopathy Detection Using Optical Coherence Tomography Angiography

      Explore TVST Journal Ophthalmology
      Ensemble Deep Learning for Diabetic Retinopathy Detection Using Optical Coherence Tomography Angiography
      Purpose : To evaluate the role of ensemble learning techniques with deep learning in classifying diabetic retinopathy (DR) in optical coherence tomography angiography (OCTA) images and their corresponding co-registered structural images. Methods : A total of 463 volumes from 380 eyes were acquired using the 3 3-mm OCTA protocol on the Zeiss Plex Elite system. Enface images of the superficial and deep capillary plexus were exported from both the optical coherence tomography ...
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      Mentions: University of British Columbia Marinko V. Sarunic Simon Fraser University

    5. Retinal capillary perfusion heterogeneity in diabetic retinopathy detected by optical coherence tomography angiography

      Explore IOVS Journal Ophthalmology
      Retinal capillary perfusion heterogeneity in diabetic retinopathy detected by optical coherence tomography angiography
      Purpose : To investigate the ability of a commercially available optical coherence tomography angiography (OCTA) machine to describe retinal capillary perfusion heterogeneity in diabetic retinopathy (DR) patients. Methods : Ten consecutive en face 6x6mm foveal OCTA images were obtained from both eyes of 13 DR patients and 5 healthy controls using a Zeiss PLEX Elite 9000. Fifteen DR and eight healthy eyes met the inclusion criteria: a centered fovea, little motion artifacts ...
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      Mentions: University of British Columbia Marinko V. Sarunic Simon Fraser University

    6. Pseudo-real-time retinal layer segmentation for high-resolution adaptive optics optical coherence tomography

      Explore arxiv.org Ophthalmology
      Pseudo-real-time retinal layer segmentation for high-resolution adaptive optics optical coherence tomography
      We present a pseudo-real-time retinal layer segmentation for high-resolution Sensorless Adaptive Optics-Optical Coherence Tomography (SAO-OCT). Our pseudo-real-time segmentation method is based on Dijkstras algorithm that uses the intensity of pixels and the vertical gradient of the image to find the minimum cost in a geometric graph formulation within a limited search region. It segments six retinal layer boundaries in an iterative process according to their order of prominence. The segmentation ...
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      Mentions: Oregon Health & Science University Marinko V. Sarunic Simon Fraser University

    7. ADAPTIVE OPTICS OPTICAL COHERENCE TOMOGRAPHY IN A CASE OF ACUTE ZONAL OCCULT OUTER RETINOPATHY

      Explore LWW Online Ophthalmology
      ADAPTIVE OPTICS OPTICAL COHERENCE TOMOGRAPHY IN A CASE OF ACUTE ZONAL OCCULT OUTER RETINOPATHY
      Purpose: To report a case of acute zonal occult outer retinopathy in which adaptive optics (AO) facilitated visualization of abnormal photoreceptors previously thought to be in an area of normal retina on conventional optical coherence tomography ( OCT ). Methods: Case report. Results: A 51-year-old woman presents with 11-month history of photopsias and scotoma in the temporal visual field of her left eye. Ocular imaging including fluorescein angiography, fundus autofluorescence and OCT ...
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      Mentions: University of British Columbia Tufts University Marinko V. Sarunic

    8. Cascaded Deep Neural Networks for Retinal Layer Segmentation of Optical Coherence Tomography with Fluid Presence

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      Cascaded Deep Neural Networks for Retinal Layer Segmentation of Optical Coherence Tomography with Fluid Presence
      Optical coherence tomography (OCT) is a non-invasive imaging technology which can provide micrometer-resolution cross-sectional images of the inner structures of the eye. It is widely used for the diagnosis of ophthalmic diseases with retinal alteration, such as layer deformation and fluid accumulation. In this paper, a novel framework was proposed to segment retinal layers with fluid presence. The main contribution of this study is two folds: 1) we developed a ...
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      Mentions: Marinko V. Sarunic Simon Fraser University Sieun Lee

    10. Multi-scale and -contrast sensorless adaptive optics optical coherence tomography

      Explore Home Ophthalmology
      Multi-scale and -contrast sensorless adaptive optics optical coherence tomography
      Background: The roles of the retinal microvasculature and the retinal pigment epithelium (RPE) in maintaining the health and metabolic activity of the retina lend great clinical value to their high-resolution visualization. Methods: By integrating polarization diversity detection (PDD) into multi-scale and -contrast sensorless adaptive optics optical coherence tomography (MSC-SAO-OCT), we have developed a novel multi-contrast SAO OCT system for imaging pigment in the RPE as well as flow in the ...
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      Mentions: Shuichi Makita Yoshiaki Yasuno Oregon Health & Science University

    11. System and method for dynamic focus control

      Explore uspto.gov Patents
      System and method for dynamic focus control
      En face views of OCT volumes provide important and complementing visualizations of the retina and optic nerve head investigating biomarkers of diseases affecting the retina. We demonstrate the combination of real time processing of OCT volumetric data for axial tracking. In combination with a Controllable Optical Element (COE), this invention demonstrates acquisition, real time tracking, automated focus on depth resolved en face layers extracted from a volume, and focus stacked ...
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      Mentions: Marinko V. Sarunic

    12. Deep-Learning based Multiclass Retinal Fluid Segmentation and Detection in Optical Coherence Tomography Images using a Fully Convolutional Neural Network

      Explore ScienceDirect Ophthalmology
      Deep-Learning based Multiclass Retinal Fluid Segmentation and Detection in Optical Coherence Tomography Images using a Fully Convolutional Neural Network
      As a non-invasive imaging modality, optical coherence tomography (OCT) can provide micrometer-resolution 3D images of retinal structures. These images can help reveal disease-related alterations below the surface of the retina, such as the presence of edema, or accumulation of fluid which can distort vision, and are an indication of disruptions in the vasculature of the retina. In this paper, a new framework is proposed for multiclass fluid segmentation and detection ...
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      Mentions: University of British Columbia Marinko V. Sarunic Simon Fraser University

    13. EN FACE OPTICAL COHERENCE TOMOGRAPHY AND OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY OF INNER RETINAL DIMPLES AFTER INTERNAL LIMITING MEMBRANE PEELING FOR FULL-THICKNESS MACULAR HOLES

      Explore LWW Online Ophthalmology
      EN FACE OPTICAL COHERENCE TOMOGRAPHY AND OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY OF INNER RETINAL DIMPLES AFTER INTERNAL LIMITING MEMBRANE PEELING FOR FULL-THICKNESS MACULAR HOLES
      Purpose: To quantitatively and qualitatively evaluate the microvascular and structural abnormalities associated with inner retinal dimpling after internal limiting membrane peeling for full-thickness macular holes using sequential en face optical coherence tomography ( OCT ) and OCT angiography. Methods: Thirteen eyes of 13 patients with idiopathic full-thickness macular holes were enrolled in the study. Patients were treated with pars plana vitrectomy , internal limiting membrane peeling, and gas tamponade. Subjects were evaluated preoperatively ...
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      Mentions: University of British Columbia Marinko V. Sarunic Simon Fraser University

    15. Automated identification of cone photoreceptors in adaptive optics optical coherence tomography images using transfer learning

      Explore OSA | OSA Publishing Ophthalmology
      Automated identification of cone photoreceptors in adaptive optics optical coherence tomography images using transfer learning
      Automated measurements of the human cone mosaic requires the identification of individual cone photoreceptors. The current gold standard, manual labeling, is a tedious process and can not be done in a clinically useful timeframe. As such, we present an automated algorithm for identifying cone photoreceptors in adaptive optics optical coherence tomography (AO-OCT) images. Our approach fine-tunes a pre-trained convolutional neural network originally trained on AO scanning laser ophthalmoscope (AO-SLO) images ...
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      Mentions: University of British Columbia Marinko V. Sarunic Simon Fraser University

    16. Visible light sensorless adaptive optics for retinal structure and fluorescence imaging

      Explore OSA | OSA Publishing Ophthalmology
      Visible light sensorless adaptive optics for retinal structure and fluorescence imaging
      Optical coherence tomography (OCT) has emerged as a powerful imaging instrument and technology in biomedicine. OCT imaging is predominantly performed using wavelengths in the near infrared; however, visible light (VIS) has been recently employed in OCT systems with encouraging results for high-resolution retinal imaging. Using a broadband supercontinuum VIS source, we present a sensorless adaptive optics (SAO) multimodal imaging system driven by VIS-OCT for volumetric retinal structural imaging, followed by ...
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      Mentions: Oregon Health & Science University Marinko V. Sarunic Simon Fraser University
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  4. About Marinko V. Sarunic

    Marinko V. Sarunic

    Marinko V. Sarunic is an Associate Professor, School of Engineering Science, Simon Fraser University, Vancouver, Canada. Dr. Marinko Sarunic is an SFU alumnus, having received a B.A.Sc. in Engineering Physics from Simon Fraser University in 1998. He continued on at SFU for a M.A.Sc. thesis, under the supervision of Dr. Glenn Chapman. In 2006, he completed a PhD at Duke University with a research focus on Fourier domain optical coherence tomography.

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