A Reparametrized CNN Model to Distinguish Alzheimer's Disease Applying Multiple Morphological Metrics and Deep Semantic Features From Structural MRI

It is of potential clinical value to improve the accuracy of Alzheimer's disease (AD) recognition using structural MRI. We proposed a reparametrized convolutional neural network (Re-CNN) to discriminate AD from NC by applying morphological metrics and deep semantic features. The deep semantic f...

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Detalles Bibliográficos
Autores principales: Chen, Zhenpeng, Mo, Xiao, Chen, Rong, Feng, Pujie, Li, Haiyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Aging Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9204294/
https://www.ncbi.nlm.nih.gov/pubmed/35721011
http://dx.doi.org/10.3389/fnagi.2022.856391

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9204294/
https://www.ncbi.nlm.nih.gov/pubmed/35721011
http://dx.doi.org/10.3389/fnagi.2022.856391

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