Browsing by Author "Hervella, Álvaro S."
Now showing items 1-20 of 23
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Color Fundus Image Registration Using a Learning-Based Domain-Specific Landmark Detection Methodology
Rivas-Villar, David; Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge (Elsevier, 2022)[Abstract] Medical imaging, and particularly retinal imaging, allows to accurately diagnose many eye pathologies as well as some systemic diseases such as hypertension or diabetes. Registering these images is crucial to ... -
ConKeD: multiview contrastive descriptor learning for keypoint-based retinal image registration
Rivas-Villar, David; Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge (Springer, 2024-07)[Abstract]: Retinal image registration is of utmost importance due to its wide applications in medical practice. In this context, we propose ConKeD, a novel deep learning approach to learn descriptors for retinal image ... -
Context encoder self-supervised approaches for eye fundus analysis
Iglesias Morís, Daniel; Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (Institute of Electrical and Electronics Engineers Inc., 2021)[Abstract]: The broad availability of medical images in current clinical practice provides a source of large image datasets. In order to use these datasets for training deep neural networks in detection and segmentation ... -
Context encoder transfer learning approaches for retinal image analysis
Iglesias Morís, Daniel; Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (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 ... -
Deep Learning Techniques for Automated Analysis and Processing of High Resolution Medical Imaging
Hervella, Álvaro S. (2022)[Abstract] Medical imaging plays a prominent role in modern clinical practice for numerous medical specialties. For instance, in ophthalmology, different imaging techniques are commonly used to visualize and study the ... -
Deep multi-instance heatmap regression for the detection of retinal vessel crossings and bifurcations in eye fundus images
Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Penedo, Manuel; Ortega Hortas, Marcos (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 ... -
Deep Multi-Segmentation Approach for the Joint Classification and Segmentation of the Retinal Arterial and Venous Trees in Color Fundus Images
Morano, José; Hervella, Álvaro S.; Novo Buján, Jorge; Rouco, J. (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. ... -
End-To-End Multi-Task Learning for Simultaneous Optic Disc and Cup Segmentation and Glaucoma Classification in Eye Fundus Images
Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (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 ... -
Enhancing Retinal Blood Vessel Segmentation through Self-Supervised Pre-Training
Morano, José; Hervella, Álvaro S.; Barreira, Noelia; Novo Buján, Jorge; Rouco, J. (MDPI AG, 2020-08-25)[Abstract] The segmentation of the retinal vasculature is fundamental in the study of many diseases. However, its manual completion is problematic, which motivates the research on automatic methods. Nowadays, these methods ... -
Explainable artificial intelligence for the automated assessment of the retinal vascular tortuosity
Hervella, Álvaro S.; Ramos, Lucía; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (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 ... -
Joint keypoint detection and description network for color fundus image registration
Rivas-Villar, David; Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge (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 ... -
Joint Optic Disc and Cup Segmentation Using Self-Supervised Multimodal Reconstruction Pre-Training
Hervella, Álvaro S.; Ramos, Lucía; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (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 ... -
Learning the Retinal Anatomy From Scarce Annotated Data Using Self-Supervised Multimodal Reconstruction
Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (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 ... -
Multi-Adaptive Optimization for multi-task learning with deep neural networks
Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (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 ... -
Multimodal Image Encoding Pre-training for Diabetic Retinopathy Grading
Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (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, ... -
Multimodal registration of retinal images using domain-specific landmarks and vessel enhancement
Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (Elsevier, 2018)[Absctract]: The analysis of different image modalities is frequently performed in ophthalmology as it provides complementary information for the diagnosis and follow-up of relevant diseases, like hypertension or diabetes. ... -
Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction
Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (M D P I AG, 2019-08-07)[Abstract] This work explores the use of paired and unpaired data for training deep neural networks in the multimodal reconstruction of retinal images. Particularly, we focus on the reconstruction of fluorescein angiography ... -
Recurrent Task Specialization Network for Segmentation-aided Vascular Landmarks Detection in Retinal Images
Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Sánchez, Clara I.; Ortega Hortas, Marcos (IOS Press, 2024-10)[Abstract]: The detection of vessel crossings and bifurcations in eye fundus images plays an important role in numerous applications, including the diagnosis of ophthalmic and systemic diseases, biometric authentication, ... -
Retinal Microaneurysms Detection Using Adversarial Pre-training With Unlabeled Multimodal Images
Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (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
Hervella, Álvaro S.; Rouco, J.; Novo Buján, Jorge; Ortega Hortas, Marcos (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 ...