Automatic macular edema identification and characterization using OCT images
Use this link to cite
http://hdl.handle.net/2183/34469
Except where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC-BY-NC-ND 4.0)
Collections
- GI-VARPA - Artigos [76]
Metadata
Show full item recordTitle
Automatic macular edema identification and characterization using OCT imagesAuthor(s)
Date
2018-09Citation
Samagaio, G., Estévez, A., Moura, J. de, Novo, J., Fernández, M. I., & Ortega, M. (2018). Automatic macular edema identification and characterization using OCT images. Computer Methods and Programs in Biomedicine, 163, 47–63. doi:10.1016/j.cmpb.2018.05.033
Is version of
https://doi.org/10.1016/j.cmpb.2018.05.033
Abstract
[Abstract]: Background and objective: The detection and characterization of the intraretinal fluid accumulation constitutes a crucial ophthalmological issue as it provides useful information for the identification and diagnosis of the different types of Macular Edema (ME). These types are clinically defined, according to the clinical guidelines, as: Serous Retinal Detachment (SRD), Diffuse Retinal Thickening (DRT) and Cystoid Macular Edema (CME). Their accurate identification and characterization facilitate the diagnostic process, determining the disease severity and, therefore, allowing the clinicians to achieve more precise analysis and suitable treatments. Methods: This paper proposes a new fully automatic system for the identification and characterization of the three types of ME using Optical Coherence Tomography (OCT) images. In the case of SRD and CME edemas, multilevel image thresholding approaches were designed and combined with the application of ad-hoc clinical restrictions. The case of DRT edemas, given their complexity and fuzzy regional appearance, was approached by a learning strategy that exploits intensity, texture and clinical-based information to identify their presence. Results: The system provided satisfactory results with F-Measures of 87.54% and 91.99% for the DRT and CME detections, respectively. In the case of SRD edemas, the system correctly detected all the cases that were included in the designed dataset. Conclusions: The proposed methodology offered an accurate performance for the individual identification and characterization of the three different types of ME in OCT images. In fact, the method is capable to handle the ME analysis even in cases of significant severity with the simultaneous existence of the three ME types that appear merged inside the retinal layers.
Keywords
Computer-aided diagnosis
Retinal imaging
Macular Edema
Optical Coherence Tomography
Retinal imaging
Macular Edema
Optical Coherence Tomography
Description
© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/. This version of the article: Samagaio, G., Estévez, A., Moura, J. de, Novo, J., Fernández, M. I., & Ortega, M. (2018). “Automatic macular edema identification and characterization using OCT images” has been accepted for publication in Computer Methods and Programs in Biomedicine, 163, 47–63. The Version of Record is available online at: https://doi.org/10.1016/j.cmpb.2018.05.033.
Editor version
Rights
Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC-BY-NC-ND 4.0)
ISSN
0169-2607