Literature DB >> 26598974

Automatic segmentation of the optic nerve head for deformation measurements in video rate optical coherence tomography.

Maribel Hidalgo-Aguirre1, Julian Gitelman2, Mark Richard Lesk3, Santiago Costantino3.   

Abstract

Optical coherence tomography (OCT) imaging has become a standard diagnostic tool in ophthalmology, providing essential information associated with various eye diseases. In order to investigate the dynamics of the ocular fundus, we present a simple and accurate automated algorithm to segment the inner limiting membrane in video-rate optic nerve head spectral domain (SD) OCT images. The method is based on morphological operations including a two-step contrast enhancement technique, proving to be very robust when dealing with low signal-to-noise ratio images and pathological eyes. An analysis algorithm was also developed to measure neuroretinal tissue deformation from the segmented retinal profiles. The performance of the algorithm is demonstrated, and deformation results are presented for healthy and glaucomatous eyes.

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Year:  2015        PMID: 26598974     DOI: 10.1117/1.JBO.20.11.116008

Source DB:  PubMed          Journal:  J Biomed Opt        ISSN: 1083-3668            Impact factor:   3.170


  2 in total

1.  Length-adaptive graph search for automatic segmentation of pathological features in optical coherence tomography images.

Authors:  Brenton Keller; David Cunefare; Dilraj S Grewal; Tamer H Mahmoud; Joseph A Izatt; Sina Farsiu
Journal:  J Biomed Opt       Date:  2016-07-01       Impact factor: 3.170

2.  Quantitative confocal optical coherence elastography for evaluating biomechanics of optic nerve head using Lamb wave model.

Authors:  Zhaodong Du; Runze Li; Xuejun Qian; Gengxi Lu; Yan Li; Youmin He; Yueqiao Qu; Laiming Jiang; Zeyu Chen; Mark S Humayun; Zhongping Chen; Qifa Zhou
Journal:  Neurophotonics       Date:  2019-11-15       Impact factor: 3.593

  2 in total

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