Authors:
A. González
;
C. Ortigueira
;
M. Ortega
and
M. G. Penedo
Affiliation:
University of A Coruña, Spain
Keyword(s):
OCT Retinal Images, Layer, Segmentation, Graph, Multiscale, Pyramidal.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
;
Vision and Perception
Abstract:
OCT technique for retinal imaging is establishing itself as a relevant modality among ophthalmologists due to its capacity to show more information than classical modalities. Nowadays, most image processing-based applications are emerging to extract that information automatically. As previous step of any automatic method to extract features from these images, the segmentation of the retinal layers has to be done. Graph-based methods provide good results for this problem, although their efficiency is an important limitation. In this work, a multiscale or pyramidal-based approach is studied in order to solve this problem. Different configurations are proposed to determine the optimal method. It is remarkable that this approach means an improvement not only in computation time, but also in segmentation results.