1. Jonathan D. Oakley

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    1. Mentioned In 26 Articles

    2. Automated Deep Learning-based Multi-class Fluid Segmentation in Swept-Source Optical Coherence Tomography Images

      Automated Deep Learning-based Multi-class Fluid Segmentation in Swept-Source Optical Coherence Tomography Images
      Purpose: To evaluate the performance of a deep learning-based, fully automated, multi-class, macular fluid segmentation algorithm relative to expert annotations in a heterogeneous population of confirmed wet age-related macular degeneration (wAMD) subjects. Methods: Twenty-two swept-source optical coherence tomography (SS-OCT) volumes of the macula from 22 from different individuals with wAMD were manually annotated by two expert graders. These results were compared using cross-validation (CV) to automated segmentations using a deep ...
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    3. Method and apparatus for generation or editing of layer delineations

      Method and apparatus for generation or editing of layer delineations
      Methods are disclosed for the generation and editing of layer delineations within three-dimensional tomography scans. Cross sections of a subject are generated and presented to an operator, who has the ability to edit layer delineations within the cross section, or determine parameters used to generate new cross sections. By guiding an operator through a set of displayed cross sections, the methods can allow for a more rapid, efficient, and error-free ...
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    4. A 3D Deep Learning System for Detecting Referable Glaucoma Using Full OCT Macular Cube Scans

      A 3D Deep Learning System for Detecting Referable Glaucoma Using Full OCT Macular Cube Scans
      Purpose : The purpose of this study was to develop a 3D deep learning system from spectral domain optical coherence tomography (SD-OCT) macular cubes to differentiate between referable and nonreferable cases for glaucoma applied to real-world datasets to understand how this would affect the performance. Methods : There were 2805 Cirrus optical coherence tomography (OCT) macula volumes (Macula protocol 512 128) of 1095 eyes from 586 patients at a single site that ...
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    5. Deep Learning for Prediction of AMD Progression: A Pilot Study

      Deep Learning for Prediction of AMD Progression: A Pilot Study
      Purpose : To develop and assess a method for predicting the likelihood of converting from early/intermediate to advanced wet age-related macular degeneration (AMD) using optical coherence tomography (OCT) imaging and methods of deep learning. Methods : Seventy-one eyes of 71 patients with confirmed early/intermediate AMD with contralateral wet AMD were imaged with OCT three times over 2 years (baseline, year 1, year 2). These eyes were divided into two groups ...
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    6. Changes in volume of various retinal layers over time in early and intermediate age-related macular degeneration

      Changes in volume of various retinal layers over time in early and intermediate age-related macular degeneration
      Purpose To evaluate longitudinally volume changes in inner and outer retinal layers in early and intermediate age-related macular degeneration (AMD) compared to healthy control eyes using optical coherence tomography (OCT). Methods 71 eyes with AMD and 31 control eyes were imaged at two time points: baseline and after 2 years. Automated OCT layer segmentation was performed using Orion TM . This software is able to measure volumes of retinal layers with ...
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    7. Automated analysis of the optic nerve head via optical coherence tomography measurements, methods and representations

      Automated analysis of the optic nerve head via optical coherence tomography measurements, methods and representations
      The present invention relates to structural analysis of the optic nerve head (ONH). In one approach, a 3D volume of intensity data which includes the optic nerve head is acquired using an optical coherence tomography (OCT) system. The vitreoretinal interface (VRI) and the optic disc margin are identified from the 3D data. The minimum area of a surface from the optic disc margin to the VRI is determined. This minimum ...
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    8. The measurement repeatability using different partition methods of intraretinal tomographic thickness maps in healthy human subjects

      The measurement repeatability using different partition methods of intraretinal tomographic thickness maps in healthy human subjects
      ...ETDRS sectors. Jia Tan,1,2,* Ye Yang,2,3,* Hong Jiang,2,4 Che Liu,2 Zhihong Deng,1,2 Byron L Lam,2 Liang Hu,3 Jonathan Oakley,5 Jianhua Wang2 1Department of Ophthalmology, Xiangya Hospital, Changsha, Hunan, People’s Repu...
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    9. Automated analysis of the optic nerve head: measurements, methods and representations

      Automated analysis of the optic nerve head: measurements, methods and representations
      The present invention relates to structural analysis of the optic nerve head (ONH). In one approach, a 3D volume of intensity data which includes the optic nerve head is acquired using an optical coherence tomography (OCT) system. The vitreoretinal interface (VRI) and the optic disc margin are identified from the 3D data. The minimum area of a surface from the optic disc margin to the VRI is determined. This minimum ...
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    10. Changes in macular layers in the early course of non-arteritic ischaemic optic neuropathy

      Changes in macular layers in the early course of non-arteritic ischaemic optic neuropathy
      Purpose To characterise the changes of the retinal layers in patients with acute anterior ischaemic optic neuropathy (AION), aiming to identify imaging markers for predicting the residual visual function. Methods This was a retrospective review of consecutive patients with unilateral AION from January 2010 to December 2013. We analysed affected eyes at baseline and 1 month later, compared to fellow healthy eyes. Utilising novel image analysis software, we conducted algorithmic ...
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    11. Voxeleron Releases Orion, Advanced OCT Analysis Software

      Voxeleron Releases Orion, Advanced OCT Analysis Software
      Orion is an application that offers fully-automated, rapid and accurate segmentation of seven layers in OCT images of the human retina. Currently for research use only, the award-winning software is platform independent - meaning it processes data from different OCT devices - and is now available following extensive beta testing. We used Orion to process a considerable amount of data and found it to be a very useful research tool. The analysis ...
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    12. Methods to reduce variance in OCT analysis of the macula

      Methods to reduce variance in OCT analysis of the macula
      Methods for analyzing optical coherence tomography (OCT) images of the macula to reduce variance and improve disease diagnosis are presented. One embodiment of the invention is directed towards selecting analysis locations and data segmentation techniques to take advantage of structural homogeneities. Another embodiment is directed towards reducing the variance in a collection of normative data by transforming the individual members of the database to correspond to a Standard Macula. Variations ...
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    13. Phoenix Research Labs Partners with Voxeleron to Advance Technology for Eye Research

      Phoenix Research Labs Partners with Voxeleron to Advance Technology for Eye Research
      ...ysis software can only strengthen their customers’ ability to effectively perform fundamental research,” said Jonathan Oakley, PhD, Co-founder and Principal at Voxeleron. “The Voxeleron algorithms offers an unparalleled...
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    14. 1-15 of 26 1 2 »
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  2. About Jonathan D. Oakley

    Jonathan D. Oakley

    Jonathan Oakley has a B.Sc. in Computer Science from the University of York, England, a Masters from the department of Medical Physics at University College, London, and a Ph.D. in medical image processing from the Swiss Federal Institute of Technology.  Since then, he has spent over ten years working on image processing algorithm development for KLA-Tencor, Fujifilm and, most recently, Carl Zeiss Meditec Inc., where he worked exclusively in OCT.  While at Zeiss, he was responsible for motion correction, image registration and various anatomical segmentation algorithms including the Optic Nerve Head as well as retinal layer segmentation algorithms, some of which have generated new scientific findings and consequently new market opportunities for ophthalmic imaging in the neurological domain.  In 2010 he and Daniel Russakoff formed Voxeleron LLC.

  3. Quotes

    1. Orion is our flagship product targeted at reading centers burdened with the laborious task of manual segmentation, CROs running clinical trials lacking relevant imaging-based biomarkers, and clinical researchers overwhelmed by data and hamstrung by the limited image analysis tools available...It is the most advanced OCT analysis software package available today, and our road map is comprehensive, including change analysis in the next release.
      In Orion is in Beta - Voxeleron prepares the release of their advanced OCT analysis software
    2. We’re very excited by the opportunity to work with Phoenix. Clearly they have a strong portfolio of technologies optimized for animal eye research, so the addition of image analysis software can only strengthen their customers’ ability to effectively perform fundamental research.
      In Phoenix Research Labs Partners with Voxeleron to Advance Technology for Eye Research