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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, ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...