Optimized Convolutional Fusion for Multimodal Neuroimaging in Alzheimer’s Disease Diagnosis: Enhancing Data Integration and Feature Extraction

Multimodal neuroimaging has gained traction in Alzheimer’s Disease (AD) diagnosis by integrating information from multiple imaging modalities to enhance classification accuracy. However, effectively handling heterogeneous data sources and overcoming the challenges posed by multiscale transform metho...

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Detalles Bibliográficos
Autores principales: Odusami, Modupe, Maskeliūnas, Rytis, Damaševičius, Robertas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10608760/
https://www.ncbi.nlm.nih.gov/pubmed/37888107
http://dx.doi.org/10.3390/jpm13101496

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10608760/
https://www.ncbi.nlm.nih.gov/pubmed/37888107
http://dx.doi.org/10.3390/jpm13101496

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