Toward A Reproducible, Scalable Framework for Processing Large Neuroimaging Datasets
Erik C. Johnson, Miller Wilt, Luis M. Rodríguez, Raphael Norman-Tenazas, Corban G. Rivera, Nathan G. Drenkow, Dean M. Kleissas, Theodore J. LaGrow, Hannah Cowley, Joseph Downs, Jordan Matelsky, Marisa Hughes, Elizabeth P. Reilly, Brock A. Wester, Eva L. Dyer, , William Gray-Roncal
The paper develops a scalable, reproducible framework for processing large neuroimaging datasets using open-source tools and standardized pipelines.
bioRxiv · Apr 22, 2019 · PreprintNeuroscience