Unsupervised MR harmonization by learning disentangled representations using information bottleneck theory

In magnetic resonance (MR) imaging, a lack of standardization in acquisition often causes pulse sequence-based contrast variations in MR images from site to site, which impedes consistent measurements in automatic analyses In this paper, we propose an unsupervised MR image harmonization approach, CA...

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Detalles Bibliográficos
Autores principales: Zuo, Lianrui, Dewey, Blake E., Liu, Yihao, He, Yufan, Newsome, Scott D., Mowry, Ellen M., Resnick, Susan M., Prince, Jerry L., Carass, Aaron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10473284/
https://www.ncbi.nlm.nih.gov/pubmed/34506916
http://dx.doi.org/10.1016/j.neuroimage.2021.118569

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10473284/
https://www.ncbi.nlm.nih.gov/pubmed/34506916
http://dx.doi.org/10.1016/j.neuroimage.2021.118569

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