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Intraretinal Fluid Detection by Means of a Densely Connected Convolutional Neural Network Using Optical Coherence Tomography Images
(MDPI AG, 2019-08-01)
[Abstract] Hereby we present a methodology with the objective of detecting retinal fluid accumulations in between the retinal layers. The methodology uses a robust Densely Connected Neural Network to classify thousands of ...
Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction
(M D P I AG, 2019-08-07)
[Abstract] This work explores the use of paired and unpaired data for training deep neural networks in the multimodal reconstruction of retinal images. Particularly, we focus on the reconstruction of fluorescein angiography ...
Portable Chest X-ray Synthetic Image Generation for the COVID-19 Screening
(MDPI, 2021)
[Abstract] The global pandemic of COVID-19 raises the importance of having fast and reliable methods to perform an early detection and to visualize the evolution of the disease in every patient, which can be assessed with ...
Deep Multi-Segmentation Approach for the Joint Classification and Segmentation of the Retinal Arterial and Venous Trees in Color Fundus Images
(MDPI, 2021)
[Abstract] The analysis of the retinal vasculature represents a crucial stage in the diagnosis of several diseases. An exhaustive analysis involves segmenting the retinal vessels and classifying them into veins and arteries. ...
Computational Radiological Screening of Patients with COVID-19 Using Chest X-ray Images from Portable Devices
(MDPI, 2021)
[Abstract] This work presents a fully automatic system for the screening of chest X-ray images from portable devices under the analysis of three different clinical categories: normal, pathological cases of pulmonary diseases ...
Multi-task Convolutional Neural Networks for the End-to-end Simultaneous Segmentation and Screening of the Epiretinal Membrane in OCT Images
(EasyChair, 2023-02-16)
[Absctract]: The Epiretinal Membrane (ERM) is an ocular pathology that causes visual distortion.
In order to detect and treat the ERM, ophthalmologists visually inspect Optical Coherence
Tomography (OCT) images.This is ...
Cycle generative adversarial network approaches to produce novel portable chest X-rays images for covid-19 diagnosis
(Institute of Electrical and Electronics Engineers Inc., 2021)
[Abstract]: Coronavirus Disease 2019 (COVID-19), declared a global pandemic by the World Health Organization, mainly affects the pulmonary tissues, playing chest X-ray images an important role for its screening and early ...
Analysis of Imbalanced Datasets in the Performance of Deep Learning Approaches for COVID-19 Screening from Chest X-ray Imaging: Impact of Sex and Age Factors
(EasyChair, 2023-02-16)
[Absctract]: In this work, we analysed 11 imbalance scenarios with female and male COVID-19 patients present in different proportions for the sex analysis, and 6 scenarios where only one specific age range was used for ...
Sistema automático para la evaluación de enfermedades neurodegenerativas en imágenes OCT mediante deep learning
(2023-12)
El Alzhéimer (AD), el temblor esencial (ET), la esclerósis múltiple (MS) o el Párkinson (PD) son enfermedades neurodegenerativas (END) que están correlacionadas con cambios en algunas capas retinales clave.
Las tomografías ...
Visualization of pathological changes in retinal layer thickness using optical coherence tomography
(Instituto de Investigación Sanitaria de Santiago (IDIS), 2023-12)
[Abstract]: Optical Coherence Tomography (OCT) is a non-invasive imaging technique that provides high-resolution cross-sectional images of biological
tissues. Biomarkers such as the thickness of retinal layers can be used ...