Browsing GI-VARPA - Congresos, conferencias, etc. by Title
Now showing items 1-20 of 44
-
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 ... -
Analysis of Separability of COVID-19 and Pneumonia in Chest X-ray Images by Means of Convolutional Neural Networks
(MDPI AG, 2020-08-21)[Abstract] The new coronavirus (COVID-19) is a disease that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). On 11 March 2020, the coronavirus outbreak has been labelled a global pandemic by the ... -
Análisis de datos multimodales para la toma de decisiones clínicas utilizando Inteligencia Artificial en el contexto de la COVID-19
(2023-12-14)[Abstract]: La COVID-19 es una enfermedad pulmonar infecciosa causante de la pandemia mundial del año 2020. En los momentos críticos de las emergencias sanitarias, el equipo médico debe tomar decisiones importantes en un ... -
Automatic Deep Learning-based Models for Retinal Layer Thickness Analysis as a Biomarker for Neurodegenerative Diseases
(ARVO (Association for Research in Vision and Ophthalmology), 2023-06)Purpose : The retina is the most accessible part of the central nervous system, allowing its non-invasive exploration and measurement. Optical Coherence Tomography (OCT) offers an objective monitoring method of progression ... -
Automatic Identification of Diabetic Macular Edema Using a Transfer Learning-Based Approach
(MDPI AG, 2019-07-31)[Abstract] This paper presents a complete system for the automatic identification of pathological Diabetic Macular Edema (DME) cases using Optical Coherence Tomography (OCT) images as source of information. To do so, the ... -
Automatic Pipeline for Detection and Classification of Phytoplankton Specimens in Digital Microscopy Images of Freshwater Samples
(MDPI, 2021)[Abstract] Phytoplankton blooming can compromise the quality of the water and its safety due to the negative effects of the toxins that some species produce. Therefore, the continuous monitoring of water sources is typically ... -
Automatic Segmentation and Visualisation of the Epirretinal Membrane in OCT Scans Using Densely Connected Convolutional Networks
(MDPI, 2021)[Abstract] The Epiretinal Membrane (ERM) is an ocular disease that appears as a fibro-cellular layer of tissue over the retina, specifically, over the Inner Limiting Membrane (ILM). It causes vision blurring and distortion, ... -
Automatic Tool for the Detection, Characterization and Intuitive Visualization of Macular Edema Regions in OCT Images
(MDPI AG, 2019-08-01)[Abstract] The methodology presented in this paper aims to detect pathological regions affected by one or more of the three clinically defined types of Diabetic Macular Edema (DME). Using representative samples extracted ... -
Automatic Wide Field Registration and Mosaicking of OCTA Images Using Vascularity Information
(Elsevier BV, 2019)[Abstract] Optical Coherence Tomography Angiography (OCTA) constitutes a novel ophthalmological image modality that is characterized for being a non-invasive capture technique that allows a profound analysis of the vascular ... -
Choroid segmentation in non-EDI OCT images of multiple sclerosis patients
(A. Leitao and L. Ramos (eds.), 2023)[Abstract]: Optical coherence tomography (OCT) is a non-invasive diagnostic technique that can image ocular structures. Recently, this imaging technique has been used to diagnose and monitor patients with multiple sclerosis ... -
Comprehensive Analysis of the Screening of COVID-19 Approaches in Chest X-ray Images from Portable Devices
(i6doc.com publication, 2021)[Abstract]: Computer-aided diagnosis plays an important role in the COVID-19 pandemic. Currently, it is recommended to use X-ray imaging to diagnose and assess the evolution in patients. Particularly, radiologists are asked ... -
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 ... -
Context encoder self-supervised approaches for eye fundus analysis
(Institute of Electrical and Electronics Engineers Inc., 2021)[Abstract]: The broad availability of medical images in current clinical practice provides a source of large image datasets. In order to use these datasets for training deep neural networks in detection and segmentation ... -
COVID-19 Lung Radiography Segmentation by Means of Multiphase Transfer Learning
(MDPI, 2021)[Abstract] COVID-19 is characterized by its impact on the respiratory system and, during the global outbreak of 2020, specific protocols had to be designed to contain its spread within hospitals. This required the use of ... -
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 ... -
Data Extraction in Insurance Photo-Inspections Using Computer Vision
(MDPI AG, 2020-08-21)[Abstract] Recent advances in computer vision and artificial intelligence allow for a better processing of complex information in many fields of human activity. One such field is vehicle expertise and inspection. This ... -
Deep feature analysis in a transfer learning approach for the automatic COVID-19 screening using chest X-ray images
(Elsevier B.V., 2023)[Abstract]: COVID-19 is a challenging disease that was declared as global pandemic in March 2020. As the main impact of this disease is located in the pulmonary regions, chest X-ray devices are very useful to understand ... -
Deep learning for segmentation of optic disc and retinal layers in peripapillary optical coherence tomography images
(Society of Photo-Optical Instrumentation Engineers (SPIE), 2023-06)[Abstract]: Optical coherence tomography (OCT) is a non-invasive technique that allows the retina to be studied with precision, the analysis of the features of its layers and other structures such as the macula or the optic ... -
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. ... -
Enhancing Retinal Blood Vessel Segmentation through Self-Supervised Pre-Training
(MDPI AG, 2020-08-25)[Abstract] The segmentation of the retinal vasculature is fundamental in the study of many diseases. However, its manual completion is problematic, which motivates the research on automatic methods. Nowadays, these methods ...