Cargando…
Improving measurement of blood-brain barrier permeability with reduced scan time using deep-learning-derived capillary input function
PURPOSE: In Dynamic contrast-enhanced MRI (DCE-MRI), Arterial Input Function (AIF) has been shown to be a significant contributor to uncertainty in the estimation of kinetic parameters. This study is to assess the feasibility of using a deep learning network to estimate local Capillary Input Functio...
Autores principales: | Bae, Jonghyun, Li, Chenyang, Masurkar, Arjun, Ge, Yulin, Kim, Sungheon Gene |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10475161/ https://www.ncbi.nlm.nih.gov/pubmed/37507078 http://dx.doi.org/10.1016/j.neuroimage.2023.120284 |
Ejemplares similares
-
Blood–spinal cord barrier pericyte reductions contribute to increased capillary permeability
por: Winkler, Ethan A, et al.
Publicado: (2012) -
Reduced white matter venous density on MRI is associated with neurodegeneration and cognitive impairment in the elderly
por: Li, Chenyang, et al.
Publicado: (2022) -
A deep learning approach to predict blood-brain barrier permeability
por: Alsenan, Shrooq, et al.
Publicado: (2021) -
Permeability of muscle capillaries to microperoxidase
por: Wissig, S. L., et al.
Publicado: (1978) -
STUDIES ON THE PERMEABILITY OF LYMPHATIC CAPILLARIES
por: Leak, Lee V.
Publicado: (1971)