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

By D. Cabrera Fernández, H. M. Salinas, C. Puliafito. Optics Express, 2005

340 citations recorded by the source corpus.

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.

Subfields: Biomedical Engineering, Ophthalmology, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/26e06f3f67ec595b0065b50b931ff32b32b95f1d

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In Ophthalmology

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal 3-D Graph Search (2008, positive): “While others have presented automated 2-D approaches for the segmentation of intraretinal layers in OCT images [4], [7], to our knowledge, this the first reported approach for the automated 3-D segmentation of intraretinal layers.”
Retinal Imaging and Image Analysis (2010, neutral): “, with a median filter as in [115]–[118] or anisotropic diffusion filter as in [120]).”
Glaucoma risk index: Automated glaucoma detection from color fundus images (2010, methodology): “The desired structural RNFL can be extracted from these depth proﬁles utilizing manual or automated segmentation techniques (Fern´andez et al. 2005).”