Listar GI-VARPA - Artigos por título
Mostrando ítems 21-40 de 76
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Carotid Ultrasound Boundary Study (CUBS): An Open Multicenter Analysis of Computerized Intima–Media Thickness Measurement Systems and Their Clinical Impact
(Elsevier, 2021)[Abstract] Common carotid intima–media thickness (CIMT) is a commonly used marker for atherosclerosis and is often computed in carotid ultrasound images. An analysis of different computerized techniques for CIMT measurement ... -
Color Fundus Image Registration Using a Learning-Based Domain-Specific Landmark Detection Methodology
(Elsevier, 2022)[Abstract] Medical imaging, and particularly retinal imaging, allows to accurately diagnose many eye pathologies as well as some systemic diseases such as hypertension or diabetes. Registering these images is crucial to ... -
Comparative study of the glistening between four intraocular lens models assessed by OCT and deep learning
(Wolters Kluwer on behalf of ASCRS and ESCRS, 2024-01)Purpose: To evaluate the glistening in 4 different models of intraocular lenses (IOLs) using optical coherence tomography (OCT) and deep learning (DL). Setting: Centro Internacional de Oftalmología Avanzada (Madrid, ... -
Comprehensive analysis of clinical data for COVID-19 outcome estimation with machine learning models
(Elsevier, 2023-07)[Abstract]: COVID-19 is a global threat for the healthcare systems due to the rapid spread of the pathogen that causes it. In such situation, the clinicians must take important decisions, in an environment where medical ... -
Comprehensive fully-automatic multi-depth grading of the clinical types of macular neovascularization in OCTA images
(Springer, 2023-08)[Abstract]: Optical Coherence Tomography Angiography or OCTA represents one of the main means of diagnosis of Age-related Macular Degeneration (AMD), the leading cause of blindness in developed countries. This eye disease ... -
Computational assessment of the retinal vascular tortuosity integrating domain-related information
(Nature Research, 2019-12-27)[Abstract] The retinal vascular tortuosity presents a valuable potential as a clinical biomarker of many relevant vascular and systemic diseases. Commonly, the existent approaches face the tortuosity quantification by means ... -
ConKeD: multiview contrastive descriptor learning for keypoint-based retinal image registration
(Springer, 2024-07)[Abstract]: Retinal image registration is of utmost importance due to its wide applications in medical practice. In this context, we propose ConKeD, a novel deep learning approach to learn descriptors for retinal image ... -
Context encoder transfer learning approaches for retinal image analysis
(Elsevier Ltd, 2023-01)[Abstract]: During the last years, deep learning techniques have emerged as powerful alternatives to solve biomedical image analysis problems. However, the training of deep neural networks usually needs great amounts of ... -
Data Augmentation Approaches Using Cycle-Consistent Adversarial Networks for Improving COVID-19 Screening in Portable Chest X-Ray Images
(Elsevier, 2021)[Abstract] The current COVID-19 pandemic, that has caused more than 100 million cases as well as more than two million deaths worldwide, demands the development of fast and accurate diagnostic methods despite the lack of ... -
Deep Convolutional Approaches for the Analysis of COVID-19 Using Chest X-Ray Images From Portable Devices
(Institute of Electrical and Electronics Engineers, 2020-10-26)[Abstract] The recent human coronavirus disease (COVID-19) is a respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Given the effects of COVID-19 in pulmonary tissues, chest ... -
Deep multi-instance heatmap regression for the detection of retinal vessel crossings and bifurcations in eye fundus images
(Elsevier, 2020-04)[Abstract]: Background and objectives:The analysis of the retinal vasculature plays an important role in the diagnosis of many ocular and systemic diseases. In this context, the accurate detection of the vessel crossings ... -
Deformable registration of multimodal retinal images using a weakly supervised deep learning approach
(Springer, 2023-03-03)[Absctract]: There are different retinal vascular imaging modalities widely used in clinical practice to diagnose different retinal pathologies. The joint analysis of these multimodal images is of increasing interest since ... -
Detection of reactions to sound via gaze and global eye motion analysis using camera streaming
(Springer, 2018-06)[Abstract]: This work is focused on the field of automatic hearing assessment for patients presenting cognitive decline or severe communication difficulties. Audiometry is a test of behavior requiring intense interaction ... -
Diabetic Macular Edema Characterization and Visualization Using Optical Coherence Tomography Images
(MDPI AG, 2020-10-31)[Abstract] Diabetic Retinopathy and Diabetic Macular Edema (DME) represent one of the main causes of blindness in developed countries. They are characterized by fluid deposits in the retinal layers, causing a progressive ... -
Does imbalance in chest X-ray datasets produce biased deep learning approaches for COVID-19 screening?
(BMC, 2022)[Abstract] Background The health crisis resulting from the global COVID-19 pandemic highlighted more than ever the need for rapid, reliable and safe methods of diagnosis and monitoring of respiratory diseases. To study ... -
End-To-End Multi-Task Learning Approaches for the Joint Epiretinal Membrane Segmentation and Screening in OCT Images
(Elsevier, 2022)[Abstract] Background and objectives The Epiretinal Membrane (ERM) is an ocular disease that can cause visual distortions and irreversible vision loss. Patient sight preservation relies on an early diagnosis and on determining ... -
End-To-End Multi-Task Learning for Simultaneous Optic Disc and Cup Segmentation and Glaucoma Classification in Eye Fundus Images
(Elsevier, 2022)[Abstract] The automated analysis of eye fundus images is crucial towards facilitating the screening and early diagnosis of glaucoma. Nowadays, there are two common alternatives for the diagnosis of this disease using deep ... -
Enhanced visualization of the retinal vasculature using depth information in OCT
(Springer, 2017-06-17)[Abstract]: Retinal vessel tree extraction is a crucial step for analyzing the microcirculation, a frequently needed process in the study of relevant diseases. To date, this has normally been done by using 2D image capture ... -
Evolutionary multi-target neural network architectures for flow void analysis in optical coherence tomography angiography
(Elsevier, 2024-03)[Abstract]: Optical coherence tomography angiography (OCTA) is a non-invasive imaging modality used to evaluate the retinal microvasculature. Recent advances in OCTA allows to visualize the blood flow within the choriocapillaris ... -
Explainable artificial intelligence for the automated assessment of the retinal vascular tortuosity
(Springer, 2024)[Abstract]: Retinal vascular tortuosity is an excessive bending and twisting of the blood vessels in the retina that is associated with numerous health conditions. We propose a novel methodology for the automated assessment ...