Literature DB >> 16092326

Delineating fluid-filled region boundaries in optical coherence tomography images of the retina.

Delia Cabrera Fernández1.   

Abstract

We evaluate the ability of a deformable model to yield accurate shape descriptions of fluid-filled regions associated with age-related macular degeneration. Calculation of retinal thickness and volume by the current optical coherence tomography (OCT) system includes fluid-filled regions or lesions along with actual retinal tissue. In order to quantify these lesions independently from the retinal tissue, they must be outlined. A deformable model was applied to OCT images of retinas demonstrating cystoids and subretinal fluid spaces. Several implementation issues were addressed in order to choose appropriate parameters. The use of a nonlinear anisotropic diffusion filter to suppress speckle noise while at the same time preserving the edges of the original image was explored. Once the contours of the lesions were outlined, quantitative analysis of the surface area and volume of the lesions was performed. The deformable model could accurately outline fluid-filled regions within the retina. The detection method tested proved effective in capturing the complexity of fluid-filled regions in OCT images. Deformable models combined with nonlinear anisotropic diffusion filtering show promise in the detection of retinal features of interest for diagnosis in clinical OCT images. Thus, fluid-filled region detection may significantly aid in analysis of treatments and diagnosis.

Mesh:

Year:  2005        PMID: 16092326     DOI: 10.1109/TMI.2005.848655

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  31 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 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

4.  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

5.  Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images.

Authors:  Pratul P Srinivasan; Leo A Kim; Priyatham S Mettu; Scott W Cousins; Grant M Comer; Joseph A Izatt; Sina Farsiu
Journal:  Biomed Opt Express       Date:  2014-09-12       Impact factor: 3.732

6.  Assessment of corneal properties based on statistical modeling of OCT speckle.

Authors:  Danilo A Jesus; D Robert Iskander
Journal:  Biomed Opt Express       Date:  2016-12-08       Impact factor: 3.732

7.  Automated volumetric segmentation of retinal fluid on optical coherence tomography.

Authors:  Jie Wang; Miao Zhang; Alex D Pechauer; Liang Liu; Thomas S Hwang; David J Wilson; Dengwang Li; Yali Jia
Journal:  Biomed Opt Express       Date:  2016-03-30       Impact factor: 3.732

8.  Stratified Sampling Voxel Classification for Segmentation of Intraretinal and Subretinal Fluid in Longitudinal Clinical OCT Data.

Authors:  Milan Sonka; Michael D Abramoff
Journal:  IEEE Trans Med Imaging       Date:  2015-03-06       Impact factor: 10.048

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.  Automated 3-D intraretinal layer segmentation of macular spectral-domain optical coherence tomography images.

Authors:  Mona Kathryn Garvin; Michael David Abràmoff; Xiaodong Wu; Stephen R Russell; Trudy L Burns; Milan Sonka
Journal:  IEEE Trans Med Imaging       Date:  2009-03-10       Impact factor: 10.048

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