Literature DB >> 31171992

ReLayer: a Free, Online Tool for Extracting Retinal Thickness From Cross-Platform OCT Images.

Giovanni Ometto1, Ismail Moghul2, Giovanni Montesano1,3,4, Andrew Hunter5, Nikolas Pontikos4,6, Pete R Jones1,4,6, Pearse A Keane4,6,7, Xiaoxuan Liu8,9, Alastair K Denniston7,8,9, David P Crabb1.   

Abstract

PURPOSE: To describe and evaluate a free, online tool for automatically segmenting optical coherence tomography (OCT) images from different devices and computing summary measures such as retinal thickness.
METHODS: ReLayer (https://relayer.online) is an online platform to which OCT scan images can be uploaded and analyzed. Results can be downloaded as plaintext (.csv) files. The segmentation method includes a novel, one-dimensional active contour model, designed to locate the inner limiting membrane, inner/outer segment, and retinal pigment epithelium. The method, designed for B-scans from Heidelberg Engineering Spectralis, was adapted for Topcon 3D OCT-2000 and OptoVue AngioVue. The method was applied to scans from healthy and pathological eyes, and was validated against segmentation by the manufacturers, the IOWA Reference Algorithms, and manual segmentation.
RESULTS: Segmentation of a B-scan took ≤1 second. In healthy eyes, mean difference in retinal thickness from ReLayer and the reference standard was below the resolution of the Spectralis and 3D OCT-2000, and slightly above the resolution of the AngioVue. In pathological eyes, ReLayer performed similarly to IOWA (P = 0.97) and better than Spectralis (P < 0.001).
CONCLUSIONS: A free online platform (ReLayer) is capable of segmenting OCT scans with similar speed, accuracy, and reliability as the other tested algorithms, but offers greater accessibility. ReLayer could represent a valuable tool for researchers requiring the full segmentation, often not made available by commercial software. TRANSLATIONAL RELEVANCE: A free online platform (ReLayer) provides free, accessible segmentation of OCT images: data often not available via existing commercial software.

Entities:  

Keywords:  image analysis; optical coherence tomography; segmentation

Year:  2019        PMID: 31171992      PMCID: PMC6543924          DOI: 10.1167/tvst.8.3.25

Source DB:  PubMed          Journal:  Transl Vis Sci Technol        ISSN: 2164-2591            Impact factor:   3.283


  14 in total

1.  Validated automatic segmentation of AMD pathology including drusen and geographic atrophy in SD-OCT images.

Authors:  Stephanie J Chiu; Joseph A Izatt; Rachelle V O'Connell; Katrina P Winter; Cynthia A Toth; Sina Farsiu
Journal:  Invest Ophthalmol Vis Sci       Date:  2012-01-05       Impact factor: 4.799

Review 2.  Retinal imaging and image analysis.

Authors:  Michael D Abràmoff; Mona K Garvin; Milan Sonka
Journal:  IEEE Rev Biomed Eng       Date:  2010

3.  Automatic segmentation of nine retinal layer boundaries in OCT images of non-exudative AMD patients using deep learning and graph search.

Authors:  Leyuan Fang; David Cunefare; Chong Wang; Robyn H Guymer; Shutao Li; Sina Farsiu
Journal:  Biomed Opt Express       Date:  2017-04-27       Impact factor: 3.732

4.  Probabilistic intra-retinal layer segmentation in 3-D OCT images using global shape regularization.

Authors:  Fabian Rathke; Stefan Schmidt; Christoph Schnörr
Journal:  Med Image Anal       Date:  2014-04-13       Impact factor: 8.545

5.  The volume of peripapillary vessels within the retinal nerve fibre layer: an optical coherence tomography angiography study of normal subjects.

Authors:  Davide Allegrini; Giovanni Montesano; Paolo Fogagnolo; Alfredo Pece; Roberta Riva; Mario R Romano; Luca Rossetti
Journal:  Br J Ophthalmol       Date:  2017-08-16       Impact factor: 4.638

6.  Segmentation of retinal OCT images using a random forest classifier.

Authors:  Andrew Lang; Aaron Carass; Elias Sotirchos; Peter Calabresi; Jerry L Prince
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2013-03-13

7.  Does the Location of Bruch's Membrane Opening Change Over Time? Longitudinal Analysis Using San Diego Automated Layer Segmentation Algorithm (SALSA).

Authors:  Akram Belghith; Christopher Bowd; Felipe A Medeiros; Naama Hammel; Zhiyong Yang; Robert N Weinreb; Linda M Zangwill
Journal:  Invest Ophthalmol Vis Sci       Date:  2016-02       Impact factor: 4.799

Review 8.  The Development, Commercialization, and Impact of Optical Coherence Tomography.

Authors:  James Fujimoto; Eric Swanson
Journal:  Invest Ophthalmol Vis Sci       Date:  2016-07-01       Impact factor: 4.799

9.  Automated Retinal Layer Segmentation Using Spectral Domain Optical Coherence Tomography: Evaluation of Inter-Session Repeatability and Agreement between Devices.

Authors:  Louise Terry; Nicola Cassels; Kelly Lu; Jennifer H Acton; Tom H Margrain; Rachel V North; James Fergusson; Nick White; Ashley Wood
Journal:  PLoS One       Date:  2016-09-02       Impact factor: 3.240

10.  Retinal layer segmentation of macular OCT images using boundary classification.

Authors:  Andrew Lang; Aaron Carass; Matthew Hauser; Elias S Sotirchos; Peter A Calabresi; Howard S Ying; Jerry L Prince
Journal:  Biomed Opt Express       Date:  2013-06-14       Impact factor: 3.732

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1.  Automatic Identification and Representation of the Cornea-Contact Lens Relationship Using AS-OCT Images.

Authors:  Pablo Cabaleiro; Joaquim de Moura; Jorge Novo; Pablo Charlón; Marcos Ortega
Journal:  Sensors (Basel)       Date:  2019-11-21       Impact factor: 3.576

2.  A recommended "minimum data set" framework for SD-OCT retinal image acquisition and analysis from the Atlas of Retinal Imaging in Alzheimer's Study (ARIAS).

Authors:  Jessica Alber; Edmund Arthur; Stuart Sinoff; Delia Cabrera DeBuc; Emily Y Chew; Lori Douquette; Wendy V Hatch; Chris Hudson; Amir Kashani; Cecelia S Lee; Stephen Montaquila; Sima Mozdbar; Leonardo Provetti Cunha; Faryan Tayyari; Gregory Van Stavern; Peter J Snyder
Journal:  Alzheimers Dement (Amst)       Date:  2020-11-01

3.  A novel quantitative analysis method for idiopathic epiretinal membrane.

Authors:  Davide Allegrini; Giovanni Montesano; Stefania Marconi; Nicoletta Rosso; Giovanni Ometto; Raffaele Raimondi; Ferdinando Auricchio; Panagiotis Tsoutsanis; Francesco Semeraro; Matteo Cacciatori; David P Crabb; Mario R Romano
Journal:  PLoS One       Date:  2021-03-17       Impact factor: 3.240

4.  Structure-Function Analysis in Macular Drusen With Mesopic and Scotopic Microperimetry.

Authors:  Giovanni Montesano; Giovanni Ometto; Bethany E Higgins; Costanza Iester; Konstantinos Balaskas; Adnan Tufail; Usha Chakravarthy; Ruth E Hogg; David P Crabb
Journal:  Transl Vis Sci Technol       Date:  2020-12-28       Impact factor: 3.283

5.  OCT Assisted Quantification of Vitreous Inflammation in Uveitis.

Authors:  Xiaoxuan Liu; Aditya U Kale; Giovanni Ometto; Giovanni Montesano; Alice J Sitch; Nicholas Capewell; Charlotte Radovanovic; Nicholas Bucknall; Nicholas A V Beare; David J Moore; Pearse A Keane; David P Crabb; Alastair K Denniston
Journal:  Transl Vis Sci Technol       Date:  2022-01-03       Impact factor: 3.283

6.  Microvasculature Segmentation and Intercapillary Area Quantification of the Deep Vascular Complex Using Transfer Learning.

Authors:  Julian Lo; Morgan Heisler; Vinicius Vanzan; Sonja Karst; Ivana Zadro Matovinović; Sven Lončarić; Eduardo V Navajas; Mirza Faisal Beg; Marinko V Šarunić
Journal:  Transl Vis Sci Technol       Date:  2020-07-10       Impact factor: 3.283

  6 in total

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