4 papers
Unsupervised training of keypoint-agnostic descriptors for flexible retinal image registration
David Rivas-Villar, Ãlvaro S. Hervella, Álvaro S. Hervella +3
Current color fundus image registration approaches are limited, among other things, by the lack of labeled data, which is even more significant in the medical domain, motivating th…
Unsupervised Deep Learning-based Keypoint Localization Estimating Descriptor Matching Performance
David Rivas-Villar, Ãlvaro S. Hervella, Álvaro S. Hervella +3
Retinal image registration, particularly for color fundus images, is a challenging yet essential task with diverse clinical applications. Existing registration methods for color fu…
ConKeD: Multiview contrastive descriptor learning for keypoint-based retinal image registration
David Rivas-Villar, Ãlvaro S. Hervella, José Rouco +1
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 des…
ConKeD++ -- Improving descriptor learning for retinal image registration: A comprehensive study of contrastive losses
David Rivas-Villar, Ãlvaro S. Hervella, José Rouco +1
Self-supervised contrastive learning has emerged as one of the most successful deep learning paradigms. In this regard, it has seen extensive use in image registration and, more re…