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http://hdl.handle.net/2183/36829

Automatic Characterization of Epiretinal Membrane in OCT Images with Supervised Training

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Baamonde_Sergio_2018_Automatic_Characterization_of_Epiretinal_Membrane_in_OCT_Images_with_Supervised_Training.pdf (317.15 KB)

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URI: http://hdl.handle.net/2183/36829
DOI: 10.3390/proceedings2181161

Publication date

2018-09

Authors

Baamonde, Sergio

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Bibliographic citation

Baamonde, S.; Moura, J.d.; Novo, J.; Barreira, N.; Ortega, M. Automatic Characterization of Epiretinal Membrane in OCT Images with Supervised Training. Proceedings 2018, 2, 1161. Presented at the XoveTIC Congress 2018. https://doi.org/10.3390/proceedings2181161

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Abstract

[Abstract]: This work presents an automatic method to characterize the presence or absence of the epiretinal membrane (ERM) in Optical Coherence Tomography (OCT) images. To this end, a predefined set of classifiers is used on multiple local-based feature vectors which represent the inner limiting membrane (ILM), the layer of the retina where the ERM can be present.

Description

Presented at the XoveTIC Congress, A Coruña, Spain, 27–28 September 2018
Extended Abstract

Keywords

Epiretinal membrane Retinal Layers Medical imaging Optical Coherence Tomography

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https://doi.org/10.3390/proceedings2181161

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Atribución 4.0 Internacional

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Atribución 4.0 Internacional

Except where otherwise noted, this item's license is described as Atribución 4.0 Internacional