Cargando…
Classification of Subcortical Vascular Cognitive Impairment Using Single MRI Sequence and Deep Learning Convolutional Neural Networks
Deep learning has great potential for imaging classification by extracting low to high-level features. Our aim was to train a convolutional neural network (CNN) with single T2-weighted FLAIR sequence to classify different cognitive performances in patients with subcortical ischemic vascular disease...
Autores principales: | Wang, Yao, Tu, Danyang, Du, Jing, Han, Xu, Sun, Yawen, Xu, Qun, Zhai, Guangtao, Zhou, Yan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6593093/ https://www.ncbi.nlm.nih.gov/pubmed/31275106 http://dx.doi.org/10.3389/fnins.2019.00627 |
Ejemplares similares
-
A Deep Learning-Based Model for Classification of Different Subtypes of Subcortical Vascular Cognitive Impairment With FLAIR
por: Chen, Qi, et al.
Publicado: (2020) -
Characterizing the Penumbras of White Matter Hyperintensities and Their Associations With Cognitive Function in Patients With Subcortical Vascular Mild Cognitive Impairment
por: Wu, Xiaowei, et al.
Publicado: (2019) -
Cerebral Blood Flow Alterations as Assessed by 3D ASL in Cognitive Impairment in Patients with Subcortical Vascular Cognitive Impairment: A Marker for Disease Severity
por: Sun, Yawen, et al.
Publicado: (2016) -
An ALE Meta-Analysis of Specific Functional MRI Studies on Subcortical Vascular Cognitive Impairment
por: Xu, Wenwen, et al.
Publicado: (2021) -
Loss of Integrity of Corpus Callosum White Matter Hyperintensity Penumbra Predicts Cognitive Decline in Patients With Subcortical Vascular Mild Cognitive Impairment
por: Qiu, Yage, et al.
Publicado: (2021)