Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization

Magnetic resonance imaging and computed tomography from multiple batches (e.g. sites, scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to obtain new insights into the human brain. However, significant confounding due to batch-related technical variation, called b...

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Detalles Bibliográficos
Autores principales: Hu, Fengling, Chen, Andrew A., Horng, Hannah, Bashyam, Vishnu, Davatzikos, Christos, Alexander-Bloch, Aaron, Li, Mingyao, Shou, Haochang, Satterthwaite, Theodore D., Yu, Meichen, Shinohara, Russell T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10257347/
https://www.ncbi.nlm.nih.gov/pubmed/37084926
http://dx.doi.org/10.1016/j.neuroimage.2023.120125

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10257347/
https://www.ncbi.nlm.nih.gov/pubmed/37084926
http://dx.doi.org/10.1016/j.neuroimage.2023.120125

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