Cargando…
The diagnostic accuracy of an intelligent and automated fundus disease image assessment system with lesion quantitative function (SmartEye) in diabetic patients
BACKGROUND: With the diabetes mellitus (DM) prevalence increasing annually, the human grading of retinal images to evaluate DR has posed a substantial burden worldwide. SmartEye is a recently developed fundus image processing and analysis system with lesion quantification function for DR screening....
Autores principales: | Xu, Yi, Wang, Yongyi, Liu, Bin, Tang, Lin, Lv, Liangqing, Ke, Xin, Ling, Saiguang, Lu, Lina, Zou, Haidong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6694694/ https://www.ncbi.nlm.nih.gov/pubmed/31412800 http://dx.doi.org/10.1186/s12886-019-1196-9 |
Ejemplares similares
-
SmartEye and Polhemus data for vestibulo–ocular reflex and optokinetic reflex model
por: Le, Anh Son, et al.
Publicado: (2018) -
A Generic Pixel Pitch Calibration Method for Fundus Camera via Automated ROI Extraction
por: Long, Tengfei, et al.
Publicado: (2022) -
Prevalence of Fundus Tessellation and Its Screening Based on Artificial Intelligence in Chinese Children: the Nanjing Eye Study
por: Huang, Dan, et al.
Publicado: (2023) -
Quantitative Fundus Autofluorescence in the Developing and Maturing Healthy Eye
por: Pröbster, Carla, et al.
Publicado: (2021) -
Quantitative Assessment of Fundus Tessellated Density and Associated Factors in Fundus Images Using Artificial Intelligence
por: Shao, Lei, et al.
Publicado: (2021)