Literature DB >> 24291205

Parametric model for the 3D reconstruction of individual fovea shape from OCT data.

Patrick Scheibe1, Anfisa Lazareva2, Ulf-Dietrich Braumann3, Andreas Reichenbach4, Peter Wiedemann2, Mike Francke5, Franziska Georgia Rauscher2.   

Abstract

As revealed by optical coherence tomography (OCT), the shape of the fovea may vary greatly among individuals. However, none of the hitherto available mathematical descriptions comprehensively reproduces all individual characteristics such as foveal depth, slope, naso-temporal asymmetry, and others. Here, a novel mathematical approach is presented to obtain a very accurate model of the complete 3D foveal surface of an individual, by utilizing recent developments in OCT. For this purpose, a new formula was developed serving as a simple but very flexible way to represent a given fovea. An extensive description of the used model parameters, as well as, of the complete method of reconstructing a foveal surface from OCT data, is presented. Noteworthy, the formula analytically provides characteristic foveal parameters and thus allows for extensive quantification. The present approach was verified on 432 OCT scans and has proved to be able to capture the whole range of asymmetric foveal shapes with high accuracy (i.e. a mean fit error of 1.40 μm).
Copyright © 2013 Elsevier Ltd. All rights reserved.

Keywords:  3D reconstruction; fovea shape; mathematical model; optical coherence tomography (OCT)

Mesh:

Year:  2013        PMID: 24291205     DOI: 10.1016/j.exer.2013.11.008

Source DB:  PubMed          Journal:  Exp Eye Res        ISSN: 0014-4835            Impact factor:   3.467


  7 in total

1.  CuBe: parametric modeling of 3D foveal shape using cubic Bézier.

Authors:  Sunil Kumar Yadav; Seyedamirhosein Motamedi; Timm Oberwahrenbrock; Frederike Cosima Oertel; Konrad Polthier; Friedemann Paul; Ella Maria Kadas; Alexander U Brandt
Journal:  Biomed Opt Express       Date:  2017-08-22       Impact factor: 3.732

2.  A sloped piecemeal Gaussian model for characterising foveal pit shape.

Authors:  Lei Liu; Wendy Marsh-Tootle; Elise N Harb; Wei Hou; Qinghua Zhang; Heather A Anderson; Thomas T Norton; Katherine K Weise; Jane E Gwiazda; Leslie Hyman
Journal:  Ophthalmic Physiol Opt       Date:  2016-11       Impact factor: 3.117

3.  Direct modeling of foveal pit morphology from distortion-corrected OCT images.

Authors:  Katharina Breher; Rajat Agarwala; Alexander Leube; Siegfried Wahl
Journal:  Biomed Opt Express       Date:  2019-08-26       Impact factor: 3.732

4.  Area and volume ratios for prediction of visual outcome in idiopathic macular hole.

Authors:  Xing-Yun Geng; Hui-Qun Wu; Jie-Hui Jiang; Kui Jiang; Jun Zhu; Yi Xu; Jian-Cheng Dong; Zhuang-Zhi Yan
Journal:  Int J Ophthalmol       Date:  2017-08-18       Impact factor: 1.779

5.  Application of an OCT data-based mathematical model of the foveal pit in Parkinson disease.

Authors:  Yin Ding; Brian Spund; Sofya Glazman; Eric M Shrier; Shahnaz Miri; Ivan Selesnick; Ivan Bodis-Wollner
Journal:  J Neural Transm (Vienna)       Date:  2014-04-20       Impact factor: 3.575

6.  FOVEA: a new program to standardize the measurement of foveal pit morphology.

Authors:  Bret A Moore; Innfarn Yoo; Luke P Tyrrell; Bedrich Benes; Esteban Fernandez-Juricic
Journal:  PeerJ       Date:  2016-04-11       Impact factor: 2.984

7.  The Fovea in Retinopathy of Prematurity.

Authors:  James D Akula; Ivana A Arellano; Emily A Swanson; Tara L Favazza; Theodore S Bowe; Robert J Munro; R Daniel Ferguson; Ronald M Hansen; Anne Moskowitz; Anne B Fulton
Journal:  Invest Ophthalmol Vis Sci       Date:  2020-09-01       Impact factor: 4.799

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.