Opthalmology
Collaborations
Complexo Hospitalario Universitario de A Coruña
Complexo Hospitalario Universitario de Santiago de Compostela
Hospital de Conxo
Hospital Naval de Ferrol
Working fields
Drusen detection
Drusen are tiny white or yellow spots associated with the age-related macular degeneration (AMD). This disease can lead to severe loss central vision and adversely affect the patient’s quality of life. We have developed an automatic methodology to detect drusen in initial stages. This methodology is based a template matching technique to find the drusen in the interest areas. Currently, our work is focused on the analysis of the drusen evolution in OCTR sequences.
Red lesion detection
Arteriolar-to-Venular Ratio Computation
The retina Arteriolar-to-Venular ratio (AVR) is a parameter that helps the diagnosis of some pathologies, such as hypertension or arteriosclerosis. It is mainly computed as the ratio between the sum of artery calibers and the sum of vein calibers in several circumferences centered at the optic disc. We are currently developing and testing an automatic methodology to compute the AVR. This methodology involves the following steps:
- Optic disc location. It is the starting point. We are testing several algorithms to perform an efficient and reliable detection to the optic disc.
- Selection of Interest Radii centered at the optic disc.
- Vessel Detection and Caliber Measurement. We have developed a methodology based on snakes to measure the vessel diameter in concentric circumferences.
- Vessel Classification into Arteries and Veins. This is the most difficult step in the whole process due to the variability within inter-patient and intra-patient vessel contrast. We are testing several techniques and classifiers in order to minimize the misclassifications.
- AVR Computation. In the final step, we compute the AVR using the information obtained in the previous steps.
OCT-A
Applications
Sirius
Public databases
VICAVR database
OCTAGON dataset
CLOUD dataset
The CLOUD dataset is a set of Optical Coherence Tomography of the Anterior Segment images (AS-OCT) used to the automatic identification and representation of the cornea-contact lens relationship. The dataset includes 112 AS-OCT images that were captured from 16 different patients. In particular, the images were obtained by an OCT Cirrus 500 scanner model of Carl Zeiss Meditec with an anterior segment module for users of scleral contact lens (SCL).
If you are interested in using the CLOUD database, please send an email to: joaquim.demoura@udc.es and you will receive an authentication password to access the database. This is intended for statistical purposes only, no private data or fee is required. If you use this image set for your work, please include a reference of CLOUD in it.
- Cabaleiro, P.; de Moura, J.; Novo, J.; Charlón, P.; Ortega, M. «Automatic Identification and Representation of the Cornea–Contact Lens Relationship Using AS-OCT Images», Sensors, 19, 5087, 2019.
Main publications
- M. Ortega, N. Barreira, J. Novo, M. G. Penedo, A. Pose-Reino, F. Gómez-Ulla, «SIRIUS: A Web-based system for retinal image analysis», International Journal of Medical Informatics, 79(10), 722-732, 2010.
- S. G. Vázquez, N. Barreira, M. G. Penedo, M. Ortega, A. Pose-Reino, «Improvements in Retinal Vessel Clustering Techniques:Towards the Automatic Computation of the Arterio Venous Ratio», Computing, Archives for Scientific Computing, 90 (3), 197-217, 2010.
- S. G. Vázquez, N. Barreira, M. G. Penedo, M. Rodríguez-Blanco, «The significance of the vessel registration for a reliable computation of arteriovenous ratio», International Conference on Image Analysis and Recognition (ICIAR), Aveiro, Portugal, June 2012. (pending of publication).
- M. Díaz, J. Novo, M. G. Penedo, M. Ortega, «Automatic extraction of vascularity measurements using OCT-A images», Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 22st International Conference, KES-2018, 126, 273-281, Belgrado, Serbia, September 2018.
- M. Díaz, J. Novo, P. Cutrín, F. Gómez-Ulla, M. G. Penedo, M. Ortega, «Automatic segmentation of the Foveal Avascular Zone in ophtalmological OCT-A images», PLoS One, 14(2), e0212364, 2019.