Lucía Ramos
Lucía Ramos
PhD Student on Computer Science, University of A Coruña, Spain
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TítuloCitado porAño
Texture and color analysis for the automatic classification of the eye lipid layer
L Ramos, M Penas, B Remeseiro, A Mosquera, N Barreira, ...
International Work-Conference on Artificial Neural Networks, 66-73, 2011
Colour texture analysis for classifying the tear film lipid layer: a comparative study
B Remeseiro, L Ramos, M Penas, E Martinez, MG Penedo, A Mosquera
2011 International Conference on Digital Image Computing: Techniques and …, 2011
Analysis of parameters for the automatic computation of the tear film break-up time test based on CCLRU standards
L Ramos, N Barreira, A Mosquera, MG Penedo, E Yebra-Pimentel, ...
Computer methods and programs in biomedicine 113 (3), 715-724, 2014
Automation of the tear film break-up time test
E Cebreiro, L Ramos, A Mosquera, N Barreira, MFG Penedo
Proceedings of the 4th International Symposium on Applied Sciences in …, 2011
Computational approach for tear film assessment based on break-up dynamics
L Ramos, N Barreira, H Pena-Verdeal, MJ Giráldez, E Yebra-Pimentel
Biosystems Engineering 138, 90-103, 2015
Diurnal variations in tear film break‐up time determined in healthy subjects by software‐assisted interpretation of tear film video recordings
H Pena‐Verdeal, C García‐Resúa, L Ramos, E Yebra‐Pimentel, ...
Clinical and Experimental Optometry 99 (2), 142-148, 2016
Adaptive parameter computation for the automatic measure of the Tear Break-Up Time.
L Ramos, N Barreira, AM González, M Currás, H Pena-Verdeal, ...
KES, 1370-1379, 2012
On the automation of the tear film non-invasive break-up test
A Carpente, L Ramos, N Barreira, MG Penedo, H Pena-Verdeal, ...
2014 IEEE 27th International Symposium on Computer-Based Medical Systems …, 2014
Automated glaucoma identification using retinal fundus images: A hybrid texture feature extraction paradigm
MRK Mookiah, UR Acharya, C Chakraborty, LC Min, EY Ng, JS Suri
Image Analysis and Modeling in Ophthalmology, 9-22, 2014
Colour texture segmentation of tear film lipid layer images
B Remeseiro-López, L Ramos, NB Rodríguez, A Mosquera, ...
International Conference on Computer Aided Systems Theory, 140-147, 2013
Retinal vascular tortuosity assessment: inter-intra expert analysis and correlation with computational measurements
L Ramos, J Novo, J Rouco, S Romeo, MD Álvarez, M Ortega
BMC medical research methodology 18 (1), 1-11, 2018
Multi-expert analysis and validation of objective vascular tortuosity measurements
L Ramos, J Novo, J Rouco, S Romeo, MD Álvarez, M Ortega
Procedia Computer Science 126, 482-489, 2018
Automatic analysis of the microaneurysm turnover in a web-based framework for retinal analysis
N Barreira, MG Penedo, S González, L Ramos, B Cancela, A González
Image Anal Model Ophthalmol, 111-128, 2014
Machine Learning Applied to Optometry Data
B Remeseiro, N Barreira, L Sánchez-Brea, L Ramos, A Mosquera
Advances in Biomedical Informatics, 123-160, 2018
Automatization of dry eye syndrome tests
MG Penedo, B Remeseiro, L Ramos, N Barreira, C García-Resúa, ...
Image Analysis and Modeling in Ophthalmology, 293, 2014
Break-up analysis of the tear film based on time, location, size and shape of the rupture area
L Ramos, N Barreira, A Mosquera, H Pena-Verdeal, E Yebra-Pimentel
International Conference Image Analysis and Recognition, 695-702, 2013
Computational approach for measuring the tear film break-up time in an unsupervised manner
L Ramos, N Barreira, A Mosquera, M Currás, H Pena-Verdeal, ...
Advanced Techniques for Knowledge Engineering and Innovative Applications …, 2013
computational assessment of the retinal vascular tortuosity integrating domain-related information
L Ramos, J Novo, J Rouco, S Romeo, MD Álvarez, M Ortega
Scientific Reports 9 (1), 1-12, 2019
Rosario Torres
D Errampalli, K Everett, L Ramos, M Mari
Postharvest Pathology of Fresh Horticultural Produce, 2019
Semi-commercial hot water treatments for control of bull’s eye rot of apples
L Hasna, KR Everett, MJ Vergara, IPS Pushparajah, PN Wood, BM Fisher, ...
New Zealand Plant Protection 72, 284-284, 2019
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