Listar GI-VARPA - Artigos por título
Mostrando ítems 39-58 de 74
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Feature Definition and Comprehensive Analysis on the Robust Identification of Intraretinal Cystoid Regions Using Optical Coherence Tomography Images
(Springer, 2022)[Abstract] Currently, optical coherence tomography is one of the most used medical imaging modalities, offering cross-sectional representations of the studied tissues. This image modality is specially relevant for the ... -
Fully Automatic Deep Convolutional Approaches for the Analysis of COVID-19 Using Chest X-Ray Images
(Elsevier, 2022)[Abstract] Covid-19 is a new infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Given the seriousness of the situation, the World Health Organization declared a global pandemic as ... -
Fully automatic detection and classification of phytoplankton specimens in digital microscopy images
(Elsevier, 2021-03)[Abstract]: Background and objective: The proliferation of toxin-producing phytoplankton species can compromise the quality of the water sources. This contamination is difficult to detect, and consequently to be ... -
Fully automatic segmentation and monitoring of choriocapillaris flow voids in OCTA images
(Elsevier, 2023)[Abstract]: Optical coherence tomography angiography (OCTA) is a non-invasive ophthalmic imaging modality that is widely used in clinical practice. Recent technological advances in OCTA allow imaging of blood flow deeper ... -
Fully-Automatic 3D Intuitive Visualization of Age-Related Macular Degeneration Fluid Accumulations in OCT Cubes
(Springer, 2022-05)[Abstract]: Age-related macular degeneration is the leading cause of vision loss in developed countries, and wet-type AMD requires urgent treatment and rapid diagnosis because it causes rapid irreversible vision loss. ... -
Generation of synthetic intermediate slices in 3D OCT cubes for improving pathology detection and monitoring
(Elsevier B.V., 2023-09)[Absctract]: OCT is a non-invasive imaging technique commonly used to obtain 3D volumes of the ocular structure. These volumes allow the monitoring of ocular and systemic diseases through the observation of subtle changes ... -
Heartbeat classification fusing temporal and morphological information of ECGs via ensemble of classifiers
(Elsevier, 2019-01)[Abstract]: A method for the automatic classification of electrocardiograms (ECG) based on the combination of multiple Support Vector Machines (SVMs) is presented in this work. The method relies on the time intervals between ... -
Image-to-image translation with Generative Adversarial Networks via retinal masks for realistic Optical Coherence Tomography imaging of Diabetic Macular Edema disorders
(Elsevier, 2023)[Abstract]: One of the main issues with deep learning is the need of a significant number of samples. We intend to address this problem in the field of Optical Coherence Tomography (OCT), specifically in the context of ... -
Intra- and Inter-expert Validation of an Automatic Segmentation Method for Fluid Regions Associated with Central Serous Chorioretinopathy in OCT Images
(Springer, 2024-02)[Absctract]: Central Serous Chorioretinopathy (CSC) is a retinal disorder caused by the accumulation of fluid, resulting in vision distortion. The diagnosis of this disease is typically performed through Optical Coherence ... -
Intraretinal fluid identification via enhanced maps using optical coherence tomography images
(Optica Publishing Group, 2018)[Abstract]: Nowadays, among the main causes of blindness in developed countries are age-related macular degeneration (AMD) and the diabetic macular edema (DME). Both diseases present, as a common symptom, the appearance ... -
Intraretinal Fluid Pattern Characterization in Optical Coherence Tomography Images
(MDPI AG, 2020-04-03)[Abstract] Optical Coherence Tomography (OCT) has become a relevant image modality in the ophthalmological clinical practice, as it offers a detailed representation of the eye fundus. This medical imaging modality is ... -
Joint Diabetic Macular Edema Segmentation and Characterization in OCT Images
(Springer, 2020-06-19)[Abstract]: The automatic identification and segmentation of edemas associated with diabetic macular edema (DME) constitutes a crucial ophthalmological issue as they provide useful information for the evaluation of the ... -
Joint keypoint detection and description network for color fundus image registration
(AME Publishing Company, 2023-07-01)[Absctract]: Background: Retinal imaging is widely used to diagnose many diseases, both systemic and eye-specific. In these cases, image registration, which is the process of aligning images taken from different viewpoints ... -
Learning the Retinal Anatomy From Scarce Annotated Data Using Self-Supervised Multimodal Reconstruction
(Elsevier BV, 2020-03-13)[Abstract] Deep learning is becoming the reference paradigm for approaching many computer vision problems. Nevertheless, the training of deep neural networks typically requires a significantly large amount of annotated ... -
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, ...