Listar GI-VARPA - Artigos por título
Mostrando ítems 55-74 de 76
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Machine learning-based WENO5 scheme
(Elsevier Ltd, 2024-08-15)[Abstract]: Machine learning (ML) is becoming a powerful tool in Computational Fluid Dynamics (CFD) to enhance the accuracy, efficiency, and automation of simulations. Currently, in the design of shock-capturing methods, ... -
Modeling, Localization, and Segmentation of the Foveal Avascular Zone on Retinal OCT-Angiography Images
(IEEE, 2020-08-17)[Absctract]: The Foveal Avascular Zone (FAZ) is a capillary-free area that is placed inside the macula and its morphology and size represent important biomarkers to detect different ocular pathologies such as diabetic ... -
Multi-Adaptive Optimization for multi-task learning with deep neural networks
(Elsevier B.V., 2024-02)[Abstract]: Multi-task learning is a promising paradigm to leverage task interrelations during the training of deep neural networks. A key challenge in the training of multi-task networks is to adequately balance the ... -
Multi-Stage Transfer Learning for Lung Segmentation Using Portable X-Ray Devices for Patients With COVID-19
(Elsevier BV, 2021-07)[Abstract] One of the main challenges in times of sanitary emergency is to quickly develop computer aided diagnosis systems with a limited number of available samples due to the novelty, complexity of the case and the ... -
Multi-task localization of the hemidiaphragms and lung segmentation in portable chest X-ray images of COVID-19 patients
(Sage, 2024-02-01)[Absctract]: Background: The COVID-19 can cause long-term symptoms in the patients after they overcome the disease. Given that this disease mainly damages the respiratory system, these symptoms are often related with ... -
Multimodal Image Encoding Pre-training for Diabetic Retinopathy Grading
(Elsevier, 2022)[Abstract] Diabetic retinopathy is an increasingly prevalent eye disorder that can lead to severe vision impairment. The severity grading of the disease using retinal images is key to provide an adequate treatment. However, ... -
Multivendor fully automatic uncertainty management approaches for the intuitive representation of DME fluid accumulations in OCT images
(Springer, 2023-01-24)[Abstract]: Diabetes represents one of the main causes of blindness in developed countries, caused by fluid accumulations in the retinal layers. The clinical literature defines the different types of diabetic macular edema ... -
NEmecum: herramienta digital de ayuda a la prescripción y dispensación de fórmulas de nutrición enteral y preparados infantiles
(Arán Ediciones, 2023)[Resumen]: Introducción: existe una amplia variedad de fórmulas o preparados de nutrición enteral y fórmulas o preparados infantiles. La consulta de información relacionada debe hacerse en las herramientas propias de cada ... -
On Strongly Inflexible Manifolds
(Oxford University Press, 2023-05)[Abstract]: An oriented closed connected -manifold is inflexible if it does not admit self-maps of unbounded degree. In addition, if all the maps from any other oriented closed connected -manifold have bounded degree, then ... -
Phytoplankton detection and recognition in freshwater digital microscopy images using deep learning object detectors
(Elsevier, 2024-02-15)[Absctract]: Water quality can be negatively affected by the presence of some toxic phytoplankton species, whose toxins are difficult to remove by conventional purification systems. This creates the need for periodic ... -
Prediction of the response to photodynamic therapy in patients with chronic central serous chorioretinopathy based on optical coherence tomography using deep learning
(Elsevier, 2022-12)[Abstract]: Purpose To assess the prediction of the response to photodynamic therapy (PDT) in chronic central serous chorioretinopathy (CSCR) based on spectral-domain optical coherence tomography (SD-OCT) images using ... -
Repeatability of choriocapillaris flow voids by optical coherence tomography angiography in central serous chorioretinopathy
(Public Library of Science, 2022-12-16)[Abstract]: Purpose: To assess the repeatability of flow signal voids (FSV) measurements of the choriocapillaris (CC) and choroid (CH) in central serous chorioretinopathy (CSCR) by Swept-Source optical coherence tomography ... -
Retinal Microaneurysms Detection Using Adversarial Pre-training With Unlabeled Multimodal Images
(Elsevier, 2022)[Abstract] The detection of retinal microaneurysms is crucial for the early detection of important diseases such as diabetic retinopathy. However, the detection of these lesions in retinography, the most widely available ... -
Retinal vascular tortuosity assessment: Inter-intra expert analysis and correlation with computational measurements
(BioMed Central, 2018-11-20)[Abstract]: Background: The retinal vascular tortuosity can be a potential indicator of relevant vascular and non-vascular diseases. However, the lack of a precise and standard guide for the tortuosity evaluation hinders ... -
Robust multi-view approaches for retinal layer segmentation in glaucoma patients via transfer learning
(AME Publishing, 2023-05-01)[Absctract]: Background: Glaucoma is the leading global cause of irreversible blindness. Glaucoma patients experience a progressive deterioration of the retinal nervous tissues that begins with a loss of peripheral vision. ... -
Robust multimodal registration of fluorescein angiography and optical coherence tomography angiography images using evolutionary algorithms
(2021)[Abstract] Optical coherence tomography angiography (OCTA) and fluorescein angiography (FA) are two different vascular imaging modalities widely used in clinical practice to diagnose and grade different relevant retinal ... -
Robust segmentation of retinal layers in optical coherence tomography images based on a multistage active contour model
(Elsevier, 2019)[Abstract]: Optical Coherence Tomography (OCT) constitutes an imaging technique that is increasing its popularity in the ophthalmology field, since it offers a more complete set of information about the main retinal ... -
Self-Supervised Multimodal Reconstruction of Retinal Images Over Paired Datasets
(Elsevier Ltd, 2020-12-15)[Abstract] Data scarcity represents an important constraint for the training of deep neural networks in medical imaging. Medical image labeling, especially if pixel-level annotations are required, is an expensive task ... -
Self-Supervised Multimodal Reconstruction Pre-training for Retinal Computer-Aided Diagnosis
(Elsevier, 2021)[Abstract] Computer-aided diagnosis using retinal fundus images is crucial for the early detection of many ocular and systemic diseases. Nowadays, deep learning-based approaches are commonly used for this purpose. However, ... -
Simultaneous Segmentation and Classification of the Retinal Arteries and Veins From Color Fundus Images
(Elsevier, 2021)[Abstract] Background and objectives: The study of the retinal vasculature represents a fundamental stage in the screening and diagnosis of many high-incidence diseases, both systemic and ophthalmic. A complete retinal ...