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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 ...
Joint Optic Disc and Cup Segmentation Using Self-Supervised Multimodal Reconstruction Pre-Training
(MDPI AG, 2020-08-20)
[Abstract]
The analysis of the optic disc and cup in retinal images is important for the early diagnosis of glaucoma. In order to improve the joint segmentation of these relevant retinal structures, we propose a novel ...
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 ...
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 ...
Deep Multi-Segmentation Approach for the Joint Classification and Segmentation of the Retinal Arterial and Venous Trees in Color Fundus Images
(MDPI, 2021)
[Abstract] The analysis of the retinal vasculature represents a crucial stage in the diagnosis of several diseases. An exhaustive analysis involves segmenting the retinal vessels and classifying them into veins and arteries. ...
Automatic Pipeline for Detection and Classification of Phytoplankton Specimens in Digital Microscopy Images of Freshwater Samples
(MDPI, 2021)
[Abstract] Phytoplankton blooming can compromise the quality of the water and its safety due to the negative effects of the toxins that some species produce. Therefore, the continuous monitoring of water sources is typically ...
Automatic Identification and Characterization of the Epiretinal Membrane in OCT Images
(Optical Society of America, 2019-07-16)
[Abstract] Optical coherence tomography (OCT) is a medical image modality that is used to capture, non-invasively, high-resolution cross-sectional images of the retinal tissue. These images constitute a suitable scenario ...
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 ...
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 ...
Automatic Segmentation and Intuitive Visualisation of the Epiretinal Membrane in 3D OCT Images Using Deep Convolutional Approaches
(IEEE, 2021)
[Abstract] Epiretinal Membrane (ERM) is a disease caused by a thin layer of scar tissue that is formed on the surface of the retina. When this membrane appears over the macula, it can cause distorted or blurred vision. ...
