Publicacións en colaboración con investigadores/as de Universidade da Coruña (90)

2024

  1. 3D Features Fusion for Automated Segmentation of Fluid Regions in CSCR Patients: An OCT-based Photodynamic Therapy Response Analysis

    JOURNAL OF IMAGING INFORMATICS IN MEDICINE

  2. Adapted generative latent diffusion models for accurate pathological analysis in chest X-ray images

    Medical and Biological Engineering and Computing, Vol. 62, Núm. 7, pp. 2189-2212

  3. Are artificial intelligence chatbots a reliable source of information about contact lenses?

    Contact Lens and Anterior Eye, Vol. 47, Núm. 2

  4. Automatic simultaneous ciliary muscle segmentation and biomarker extraction in AS-OCT images using deep learning-based approaches

    Biomedical Signal Processing and Control, Vol. 90

  5. Comparative study of the glistening between four intraocular lens models assessed by OCT and deep learning

    Journal of Cataract and Refractive Surgery, Vol. 50, Núm. 1, pp. 37-42

  6. Efficient clinical decision-making process via AI-based multimodal data fusion: A COVID-19 case study

    Heliyon, Vol. 10, Núm. 20

  7. Evolutionary multi-target neural network architectures for flow void analysis in optical coherence tomography angiography

    Applied Soft Computing, Vol. 153

  8. Intra- and Inter-expert Validation of an Automatic Segmentation Method for Fluid Regions Associated with Central Serous Chorioretinopathy in OCT Images

    JOURNAL OF IMAGING INFORMATICS IN MEDICINE, Vol. 37, Núm. 1, pp. 107-122

  9. Multi-task localization of the hemidiaphragms and lung segmentation in portable chest X-ray images of COVID-19 patients

    Digital Health, Vol. 10

2023

  1. 2022 the 4th International Conference on Modeling, Simulation, Optimization and Algorithm[ICMSOA 2022], 12 November, 2022

    Journal of Physics: Conference Series

  2. A new generative approach for optical coherence tomography data scarcity: unpaired mutual conversion between scanning presets

    Medical and Biological Engineering and Computing, Vol. 61, Núm. 5, pp. 1093-1112

  3. Automatic Segmentation of Retinal Layers in Multiple Neurodegenerative Disorder Scenarios

    IEEE Journal of Biomedical and Health Informatics, Vol. 27, Núm. 11, pp. 5483-5494

  4. Comprehensive analysis of clinical data for COVID-19 outcome estimation with machine learning models

    Biomedical Signal Processing and Control, Vol. 84

  5. Comprehensive fully-automatic multi-depth grading of the clinical types of macular neovascularization in OCTA images

    Applied Intelligence, Vol. 53, Núm. 21, pp. 25897-25918

  6. Computerized tool for the automatic segmentation of DRT edemas using OCT scans

    Photo Acoustic and Optical Coherence Tomography Imaging, Volume 1: Diabetic retinopathy (Institute of Physics Publishing), pp. 1

  7. Deep feature analysis in a transfer learning approach for the automatic COVID-19 screening using chest X-ray images

    Procedia Computer Science

  8. Explainable learning to analyze the outcome of COVID-19 patients using clinical data

    Procedia Computer Science

  9. Fully automatic segmentation and monitoring of choriocapillaris flow voids in OCTA images

    Computerized Medical Imaging and Graphics, Vol. 104

  10. Image-to-image translation with Generative Adversarial Networks via retinal masks for realistic Optical Coherence Tomography imaging of Diabetic Macular Edema disorders

    Biomedical Signal Processing and Control, Vol. 79

  11. Multivendor fully automatic uncertainty management approaches for the intuitive representation of DME fluid accumulations in OCT images

    Medical and Biological Engineering and Computing, Vol. 61, Núm. 5, pp. 1209-1224