QSIPrep: an integrative platform for preprocessing and reconstructing diffusion MRI data

Autor: Valerie J. Sydnor, Eleftherios Garyfallidis, Matthew Cieslak, Raquel E. Gur, Xiaosong He, Scott T. Grafton, John A. Detre, Jason D. Yeatman, David R. Roalf, Theodore D. Satterthwaite, Barry Giesbrecht, Shreyas Fadnavis, Philip A. Cook, Michael P. Milham, Christos Davatzikos, Richard F. Betzel, Anders Perrone, Damien A. Fair, Danielle S. Bassett, Jean M. Vettel, Ariel Rokem, Eric Earl, Geoffrey K. Aguirre, Bart Larsen, Will Foran, Desmond J. Oathes, Azeez Adebimpe, Panagiotis Fotiadis, Ursula A. Tooley, Fang-Cheng Yeh, Thijs Dhollander, Laura M. Cabral, Tinashe M. Tapera, Josiane Bourque, Max B. Kelz, Adam Richie-Halford, Mark A. Elliott, Ruben C. Gur, Beatriz Luna, Adam Pines, Anisha Keshavan, Allyson P. Mackey
Rok vydání: 2021
Předmět:
Zdroj: Nat Methods
Nature methods, vol 18, iss 7
ISSN: 1548-7105
1548-7091
DOI: 10.1038/s41592-021-01185-5
Popis: 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. QSIPrep is a software platform for processing of most diffusion MRI datasets and ensures that adequate workflows are used.
Databáze: OpenAIRE