Listar GI-VARPA - Artigos por título
Mostrando ítems 17-36 de 76
-
Automatic segmentation of the foveal avascular zone in ophthalmological OCT-A images
(Public Library of Science, 2019-02-22)[Abstract]: Angiography by Optical Coherence Tomography (OCT-A) is a non-invasive retinal imaging modality of recent appearance that allows the visualization of the vascular structure at predefined depths based on the ... -
Automatic simultaneous ciliary muscle segmentation and biomarker extraction in AS-OCT images using deep learning-based approaches
(Elsevier, 2024-04)[Abstract]: Recent clinical studies have emphasized the importance of understanding the morphology and mechanics of the ciliary muscle. The ciliary muscle plays a vital role in various functions related to the anterior ... -
Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies
(M D P I AG, 2019-10-31)[Abstract] Optical Coherence Tomography Angiography (OCTA) constitutes a new non-invasive ophthalmic image modality that allows the precise visualization of the micro-retinal vascularity that is commonly used to analyze ... -
Automorphism groups of Cayley evolution algebras
(Springer, 2023-03-08)[Abstract]: In this paper we introduce a new species of evolution algebras that we call Cayley evolution algebras. We show that if a field k contains sufficiently many elements (for example if k is infinite) then every ... -
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 ...