Publicacións en colaboración con investigadores/as de Universidade da Coruña (31)

2024

  1. Explainable artificial intelligence for the automated assessment of the retinal vascular tortuosity

    Medical and Biological Engineering and Computing, Vol. 62, Núm. 3, pp. 865-881

  2. Machine learning-based WENO5 scheme

    Computers and Mathematics with Applications, Vol. 168, pp. 84-99

2023

  1. Computer-assisted evaluation of retinal vessel tortuosity in moderate-to-late preterm children

    European Journal of Ophthalmology, Vol. 33, Núm. 5, pp. 1874-1882

2022

  1. Robust Deep Learning-Based Approach for Retinal Layer Segmentation in Optical Coherence Tomography Images

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Validation of a New Software Application for Tear Breakup Measurement

    Optometry and Vision Science, Vol. 99, Núm. 2, pp. 159-166

2021

  1. Computational Radiological Screening of Patients with COVID-19 Using Chest X-ray Images from Portable Devices †

    Engineering Proceedings, Vol. 7, Núm. 1

  2. Estrategias para mejorar la participación de los estudiantes en la docencia síncrona en asignaturas del Máster Interuniversitario en Visión por Computador

    Contextos universitarios transformadores. A nova normalidade académica. Leccións aprendidas e retos de futuro: V Xornadas de innovación docente

2020

  1. Deep convolutional approaches for the analysis of Covid-19 using chest X-ray images from portable devices

    IEEE Access, Vol. 8, pp. 195594-195607

  2. Multi-Modal Self-Supervised Pre-Training for Joint Optic Disc and Cup Segmentation in Eye Fundus Images

    ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

2019

  1. A review on IoT deep learning UAV systems for autonomous obstacle detection and collision avoidance

    Remote Sensing, Vol. 11, Núm. 18

  2. Computational assessment of the retinal vascular tortuosity integrating domain-related information

    Scientific Reports, Vol. 9, Núm. 1

2018

  1. Hydra, a computer-based platform for aiding clinicians in cardiovascular analysis and diagnosis

    Journal of Visualized Experiments, Vol. 2018, Núm. 139

  2. Machine Learning Applied to Optometry Data

    Intelligent Systems Reference Library (Springer Science and Business Media Deutschland GmbH), pp. 123-160

  3. Multi-expert analysis and validation of objective vascular tortuosity measurements

    Procedia Computer Science

  4. Retinal vascular tortuosity assessment: Inter-intra expert analysis and correlation with computational measurements

    BMC Medical Research Methodology, Vol. 18, Núm. 1

2016

  1. Diurnal variations in tear film break-up time determined in healthy subjects by software-assisted interpretation of tear film video recordings

    Clinical and Experimental Optometry, Vol. 99, Núm. 2, pp. 142-148

2015

  1. Computational approach for tear film assessment based on break-up dynamics

    Biosystems Engineering, Vol. 138, pp. 90-103

2014

  1. Analysis of parameters for the automatic computation of the tear film break-up time test based on CCLRU standards

    Computer Methods and Programs in Biomedicine, Vol. 113, Núm. 3, pp. 715-724

  2. Automatic analysis of the microaneurysm turnover in a web-based framework for retinal analysis

    Image Analysis and Modeling in Ophthalmology (CRC Press), pp. 111-128

  3. Automatic assessment of tear film break-up dynamics

    Studies in Health Technology and Informatics