Cargando…
Predicting Aging of Brain Metabolic Topography Using Variational Autoencoder
Predicting future brain topography can give insight into neural correlates of aging and neurodegeneration. Due to variability in the aging process, it has been challenging to precisely estimate brain topographical change according to aging. Here, we predict age-related brain metabolic change by gene...
Autores principales: | Choi, Hongyoon, Kang, Hyejin, Lee, Dong Soo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6052253/ https://www.ncbi.nlm.nih.gov/pubmed/30050430 http://dx.doi.org/10.3389/fnagi.2018.00212 |
Ejemplares similares
-
Maturation of metabolic connectivity of the adolescent rat brain
por: Choi, Hongyoon, et al.
Publicado: (2015) -
Image-level trajectory inference of tau pathology using variational autoencoder for Flortaucipir PET
por: Hong, Jimin, et al.
Publicado: (2022) -
Toward a more informative representation of the fetal–neonatal brain connectome using variational autoencoder
por: Kim, Jung-Hoon, et al.
Publicado: (2023) -
Deep learning only by normal brain PET identify unheralded brain anomalies
por: Choi, Hongyoon, et al.
Publicado: (2019) -
Brain Plasticity Can Predict the Cochlear Implant Outcome in Adult-Onset Deafness
por: Han, Ji-Hye, et al.
Publicado: (2019)