Literature DB >> 19503235

Automated detection of retinal layer structures on optical coherence tomography images.

Delia Cabrera Fernández, Harry M Salinas, Carmen A Puliafito.   

Abstract

Segmentation of retinal layers from OCT images is fundamental to diagnose the progress of retinal diseases. In this study we show that the retinal layers can be automatically and/or interactively located with good accuracy with the aid of local coherence information of the retinal structure. OCT images are processed using the ideas of texture analysis by means of the structure tensor combined with complex diffusion filtering. Experimental results indicate that our proposed novel approach has good performance in speckle noise removal, enhancement and segmentation of the various cellular layers of the retina using the STRATUSOCTTM system.

Entities:  

Year:  2005        PMID: 19503235     DOI: 10.1364/opex.13.010200

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  80 in total

1.  Improving image segmentation performance and quantitative analysis via a computer-aided grading methodology for optical coherence tomography retinal image analysis.

Authors:  Delia Cabrera Debuc; Harry M Salinas; Sudarshan Ranganathan; Erika Tátrai; Wei Gao; Meixiao Shen; Jianhua Wang; Gábor M Somfai; Carmen A Puliafito
Journal:  J Biomed Opt       Date:  2010 Jul-Aug       Impact factor: 3.170

Review 2.  Retinal imaging and image analysis.

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

3.  Automated segmentation of intramacular layers in Fourier domain optical coherence tomography structural images from normal subjects.

Authors:  Xusheng Zhang; Siavash Yousefi; Lin An; Ruikang K Wang
Journal:  J Biomed Opt       Date:  2012-04       Impact factor: 3.170

4.  Automated quantification of lung structures from optical coherence tomography images.

Authors:  Alex M Pagnozzi; Rodney W Kirk; Brendan F Kennedy; David D Sampson; Robert A McLaughlin
Journal:  Biomed Opt Express       Date:  2013-10-09       Impact factor: 3.732

5.  Stochastic speckle noise compensation in optical coherence tomography using non-stationary spline-based speckle noise modelling.

Authors:  Andrew Cameron; Dorothy Lui; Ameneh Boroomand; Jeffrey Glaister; Alexander Wong; Kostadinka Bizheva
Journal:  Biomed Opt Express       Date:  2013-08-28       Impact factor: 3.732

6.  Kernel regression based segmentation of optical coherence tomography images with diabetic macular edema.

Authors:  Stephanie J Chiu; Michael J Allingham; Priyatham S Mettu; Scott W Cousins; Joseph A Izatt; Sina Farsiu
Journal:  Biomed Opt Express       Date:  2015-03-09       Impact factor: 3.732

7.  Motorized Micro-Forceps with Active Motion Guidance based on Common-Path SSOCT for Epiretinal Membranectomy.

Authors:  Gyeong Woo Cheon; Berk Gonenc; Russell H Taylor; Peter L Gehlbach; Jin U Kang
Journal:  IEEE ASME Trans Mechatron       Date:  2017-09-05       Impact factor: 5.303

8.  Reliability and reproducibility of macular segmentation using a custom-built optical coherence tomography retinal image analysis software.

Authors:  Delia Cabrera DeBuc; Gábor Márk Somfai; Sudarshan Ranganathan; Erika Tátrai; Mária Ferencz; Carmen A Puliafito
Journal:  J Biomed Opt       Date:  2009 Nov-Dec       Impact factor: 3.170

9.  Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search.

Authors:  Mona K Garvin; Michael D Abramoff; Randy Kardon; Stephen R Russell; Xiaodong Wu; Milan Sonka
Journal:  IEEE Trans Med Imaging       Date:  2008-10       Impact factor: 10.048

10.  Multilayered Deep Structure Tensor Delaunay Triangulation and Morphing Based Automated Diagnosis and 3D Presentation of Human Macula.

Authors:  Taimur Hassan; M Usman Akram; Mahmood Akhtar; Shoab Ahmad Khan; Ubaidullah Yasin
Journal:  J Med Syst       Date:  2018-10-04       Impact factor: 4.460

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