Name
Abstract | ||
|---|---|---|
At the present, Optical Coherence Tomography (OCT) is a very promising imaging technique used by ophthalmologists for diagnosing because it provides more information than other classical modalities. Retinal structures can be studied on these images, so image processing-based methods are emerging to extract their information. Previously to any automatic feature extraction process, delimitation of retinal layers must be automated. With that purpose, this paper presents an active contour-based method to segment retinal layer boundaries. Regarding previous work, it is remarkable that this proposal includes processes of refinement for segmented layers. Thus, validation done by an opthalmologic expert shows that the method obtains accurate results even when some of these layers present alterations or low definition, making it robust, which is a very important feat. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-11755-3_38 | IMAGE ANALYSIS AND RECOGNITION, ICIAR 2014, PT II |
Field | DocType | Volume |
Active contour model,Computer vision,Optical coherence tomography,Diabetic macular edema,Pattern recognition,Computer science,Segmentation,Image processing,Feature extraction,Artificial intelligence,Retinal | Conference | 8815 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ana González-López | 1 | 0 | 0.68 |
| M Ortega | 2 | 235 | 37.13 |
| Manuel G. Penedo | 3 | 1 | 1.03 |
| Pablo Charlón | 4 | 9 | 2.27 |