no code implementations • 25 Apr 2024 • David Rivas-Villar, Álvaro S. Hervella, José Rouco, Jorge Novo
In this work, we propose to test and extend and improve a state-of-the-art framework for color fundus image registration, ConKeD.
no code implementations • 11 Jan 2024 • David Rivas-Villar, Álvaro S. Hervella, José Rouco, Jorge Novo
In this context, we propose ConKeD, a novel deep learning approach to learn descriptors for retinal image registration.
no code implementations • 1 Dec 2022 • José Morano, Álvaro S. Hervella, José Rouco, Jorge Novo, José I. Fernández-Vigo, Marcos Ortega
This is possible thanks to the use of a CNN with a custom setting that links the lesions and the diagnosis.
no code implementations • 20 Sep 2022 • José Morano, Álvaro S. Hervella, Jorge Novo, José Rouco
The proposed multi-segmentation method allows to detect more vessels and better segment the different structures, while achieving a competitive classification performance.
no code implementations • 22 May 2022 • José Morano, Álvaro S. Hervella, José Rouco, Jorge Novo, José I. Fernández-Vigo, Marcos Ortega
To overcome these issues, several works have proposed automatic methods for the detection of AMD in retinography images, the most widely used modality for the screening of the disease.
no code implementations • 18 Dec 2020 • José Morano, Álvaro S. Hervella, Noelia Barreira, Jorge Novo, José Rouco
These two issues become specially relevant when applying FCNs to medical image segmentation as, first, the existent models are usually adjusted from broad domain applications over photographic images, and second, the amount of annotated data is usually scarcer.
no code implementations • 2 Mar 2018 • Álvaro S. Hervella, José Rouco, Jorge Novo, Marcos Ortega
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.