Cargando…
Early detection of diabetic retinopathy based on deep learning and ultra-wide-field fundus images
Visually impaired and blind people due to diabetic retinopathy were 2.6 million in 2015 and estimated to be 3.2 million in 2020 globally. Though the incidence of diabetic retinopathy is expected to decrease for high-income countries, detection and treatment of it in the early stages are crucial for...
Autores principales: | Oh, Kangrok, Kang, Hae Min, Leem, Dawoon, Lee, Hyungyu, Seo, Kyoung Yul, Yoon, Sangchul |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820327/ https://www.ncbi.nlm.nih.gov/pubmed/33479406 http://dx.doi.org/10.1038/s41598-021-81539-3 |
Ejemplares similares
-
ULTRA–WIDE-FIELD IMAGING AND INTRAVENOUS FUNDUS FLUORESCEIN ANGIOGRAPHY IN INFANTS WITH RETINOPATHY OF PREMATURITY
por: Mao, Jianbo, et al.
Publicado: (2020) -
Assessment of diabetic retinopathy using two ultra-wide-field fundus imaging systems, the Clarus® and Optos™ systems
por: Hirano, Takao, et al.
Publicado: (2018) -
Deep Learning-based Prediction of Axial Length Using Ultra-widefield Fundus Photography
por: Oh, Richul, et al.
Publicado: (2023) -
Deep-Learning-Based Hemoglobin Concentration Prediction and Anemia Screening Using Ultra-Wide Field Fundus Images
por: Zhao, Xinyu, et al.
Publicado: (2022) -
Accuracy of Diabetic Retinopathy Staging with a Deep Convolutional Neural Network Using Ultra-Wide-Field Fundus Ophthalmoscopy and Optical Coherence Tomography Angiography
por: Nagasawa, Toshihiko, et al.
Publicado: (2021)