Open AccessQSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data
Author(s) -
Matthew Cieslak,
Philip A. Cook,
Xiaosong He,
FangCheng Yeh,
Thijs Dhollander,
Azeez Adebimpe,
Geoffrey K. Aguirre,
Danielle S. Bassett,
Richard F. Betzel,
Josiane Bourque,
Laura Cabral,
Christos Davatzikos,
John A. Detre,
Eric Earl,
Mark A. Elliott,
Shreyas Fadnavis,
Damien A. Fair,
Will Foran,
Panagiotis Fotiadis,
Eleftherios Garyfallidis,
Barry Giesbrecht,
Ruben C. Gur,
Raquel E. Gur,
Max B. Kelz,
Anisha Keshavan,
Bart Larsen,
Beatríz Luna,
Allyson P. Mackey,
Michael P. Milham,
Desmond J. Oathes,
Anders Perrone,
Adam Pines,
David R. Roalf,
Adam Richie-Halford,
Ariel Rokem,
Valerie J. Sydnor,
Tinashe M. Tapera,
Ursula A. Tooley,
Jean M. Vettel,
Jason D. Yeatman,
Scott T. Grafton,
Theodore D. Satterthwaite
Publication year - 2021
Publication title -
nature methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 19.469
H-Index - 318
eISSN - 1548-7105
pISSN - 1548-7091
DOI - 10.1038/s41592-021-01185-5
Subject(s) - preprocessor , workflow , diffusion mri , computer science , software , diffusion , data mining , set (abstract data type) , artificial intelligence , sampling (signal processing) , magnetic resonance imaging , pattern recognition (psychology) , computer vision , database , physics , medicine , radiology , thermodynamics , filter (signal processing) , programming language
Diffusion-weighted magnetic resonance imaging (dMRI) is the primary method for noninvasively studying the organization of white matter in the human brain. Here we introduce QSIPrep, an integrative software platform for the processing of diffusion images that is compatible with nearly all dMRI sampling schemes. Drawing on a diverse set of software suites to capitalize on their complementary strengths, QSIPrep facilitates the implementation of best practices for processing of diffusion images.