J. de Moura

发表

Fully automatic deep convolutional approaches for the analysis of COVID-19 using chest X-ray images

M. Ortega, J. Novo, J. de Moura, 2020, Applied Soft Computing.

Does imbalance in chest X-ray datasets produce biased deep learning approaches for COVID-19 screening?

M. Ortega, J. Novo, L. Álvarez-Rodríguez, 2021, BMC Medical Research Methodology.

Fully-automatic segmentation of the ciliary muscle using anterior segment optical coherence tomography images

M. Ortega, J. Novo, J. Fernández-Vigo, 2022, 2022 International Joint Conference on Neural Networks (IJCNN).

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

Manuel G. Penedo, M. Ortega, J. Novo, 2023, Biomed. Signal Process. Control..

Unsupervised contrastive unpaired image generation approach for improving tuberculosis screening using chest X-ray images

Daniel I. Morís, M. Ortega, J. Novo, 2022, Pattern Recognit. Lett..

Automatic Segmentation and Intuitive Visualisation of the Epiretinal Membrane in 3D OCT Images Using Deep Convolutional Approaches

Marcos Ortega, Jorge Novo, Pablo Charlón, 2021, IEEE Access.

COVID-19 Lung Radiography Segmentation by Means of Multiphase Transfer Learning

M. Ortega, J. Novo, J. de Moura, 2021, Engineering Proceedings.

Robust segmentation of retinal layers in optical coherence tomography images based on a multistage active contour model

M. G. Penedo, M.G. Penedo, M. Ortega, 2019, Heliyon.

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

M. Ortega, J. Novo, J. D. Moura, 2023, Biomedical Signal Processing and Control.

Deep Convolutional Approaches for the Analysis of COVID-19 Using Chest X-Ray Images From Portable Devices

J. de Moura, L. Ramos, P. L. Vidal, 2020, IEEE Access.

Joint Diabetic Macular Edema Segmentation and Characterization in OCT Images

Marcos Ortega, Jorge Novo, Gabriela Samagaio, 2020, Journal of Digital Imaging.

Automatic identification and characterization of the epiretinal membrane in OCT images.

Marcos Ortega, Jorge Novo, Pablo Charlón, 2019, Biomedical optics express.

Portable Chest X-ray Synthetic Image Generation for the COVID-19 Screening

M. Ortega, J. Novo, J. de Moura, 2021, Engineering Proceedings.

Automatic Segmentation and Visualisation of the Epirretinal Membrane in OCT Scans Using Densely Connected Convolutional Networks

Marcos Ortega, Jorge Novo, Pablo Charlón, 2021, Engineering Proceedings.

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

M. Ortega, J. Novo, Mateo Gende, 2023, Medical & Biological Engineering & Computing.

Intraretinal fluid identification via enhanced maps using optical coherence tomography images.

Marcos Ortega, Jorge Novo, M. G. Penedo, 2018, Biomedical optics express.

Robust multi-view approaches for retinal layer segmentation in glaucoma patients via transfer learning

M. Ortega, J. Novo, J. García-Feijóo, 2023, Quantitative imaging in medicine and surgery.

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

M. Ortega, J. Novo, J. de Moura, 2023, International Conference on Knowledge-Based Intelligent Information & Engineering Systems.

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

M. Ortega, J. Novo, J. de Moura, 2023, KES.