Cargando…
Prediction of White Matter Hyperintensity in Brain MRI Using Fundus Photographs via Deep Learning
Purpose: We investigated whether a deep learning algorithm applied to retinal fundoscopic images could predict cerebral white matter hyperintensity (WMH), as represented by a modified Fazekas scale (FS), on brain magnetic resonance imaging (MRI). Methods: Participants who had undergone brain MRI and...
Autores principales: | Cho, Bum-Joo, Lee, Minwoo, Han, Jiyong, Kwon, Soonil, Oh, Mi Sun, Yu, Kyung-Ho, Lee, Byung-Chul, Kim, Ju Han, Kim, Chulho |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9224833/ https://www.ncbi.nlm.nih.gov/pubmed/35743380 http://dx.doi.org/10.3390/jcm11123309 |
Ejemplares similares
-
Semisupervised white matter hyperintensities segmentation on MRI
por: Huang, Fan, et al.
Publicado: (2022) -
Hemispheric Asymmetry of White Matter Hyperintensity in Association With Lacunar Infarction
por: Ryu, Wi‐Sun, et al.
Publicado: (2018) -
DEWS (DEep White matter hyperintensity Segmentation framework): A fully automated pipeline for detecting small deep white matter hyperintensities in migraineurs
por: Park, Bo-yong, et al.
Publicado: (2018) -
The orbitofrontal cortex functionally links obesity and white matter hyperintensities
por: Park, Bo-yong, et al.
Publicado: (2020) -
Is antiplatelet treatment effective at attenuating the progression of white matter hyperintensities?
por: Yoon, Cindy W., et al.
Publicado: (2017)