Buscar
Mostrando ítems 1-5 de 5
Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction
(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 ...
Enhancing Retinal Blood Vessel Segmentation through Self-Supervised Pre-Training
(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 ...
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 ...
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. ...
Context encoder self-supervised approaches for eye fundus analysis
(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 ...