Cargando…
Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data()
While aggregation of neuroimaging datasets from multiple sites and scanners can yield increased statistical power, it also presents challenges due to systematic scanner effects. This unwanted technical variability can introduce noise and bias into estimation of biological variability of interest. We...
Autores principales: | Beer, Joanne C., Tustison, Nicholas J., Cook, Philip A., Davatzikos, Christos, Sheline, Yvette I., Shinohara, Russell T., Linn, Kristin A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605103/ https://www.ncbi.nlm.nih.gov/pubmed/32640273 http://dx.doi.org/10.1016/j.neuroimage.2020.117129 |
Ejemplares similares
-
A multi-scanner neuroimaging data harmonization using RAVEL and ComBat
por: Torbati, Mahbaneh Eshaghzadeh, et al.
Publicado: (2021) -
Improved generalized ComBat methods for harmonization of radiomic features
por: Horng, Hannah, et al.
Publicado: (2022) -
Harmonization of multi-site diffusion tensor imaging data for cervical and thoracic spinal cord at 1.5 T and 3 T using longitudinal ComBat
por: Middleton, Devon M., et al.
Publicado: (2023) -
Validation of cross-sectional and longitudinal ComBat harmonization methods for magnetic resonance imaging data on a travelling subject cohort
por: Richter, Sophie, et al.
Publicado: (2022) -
Generalized ComBat harmonization methods for radiomic features with multi-modal distributions and multiple batch effects
por: Horng, Hannah, et al.
Publicado: (2022)