Buscar
Mostrando ítems 1-10 de 11
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, ...
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 ...
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 ...
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 ...
Weakly-supervised detection of AMD-related lesions in color fundus images using explainable deep learning
(Elsevier Ireland Ltd, 2023-02)
[Abstract]: Background and Objectives: Age-related macular degeneration (AMD) is a degenerative disorder affecting the macula, a key area of the retina for visual acuity. Nowadays, AMD is the most frequent cause of blindness ...
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 ...
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, ...
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 ...
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 ...
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 ...