Litcius/Paper detail

Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners

Rafael Garcia‐Dias, Cristina Scarpazza, Lea Baecker, Sandra Vieira, Walter Hugo Lopez Pinaya, Aiden Corvin, Alberto Redolfi, Barnaby Nelson, Benedicto Crespo‐Facorro, Colm McDonald, Diana Tordesillas‐Gutiérrez, Dara M. Cannon, David Mothersill, Dennis Hernaus, Derek W. Morris, Esther Setién‐Suero, Gary Donohoe, Giovanni B. Frisoni, Giulia Tronchin, João Ricardo Sato, Machteld Marcelis, Matthew J. Kempton, Neeltje E.M. van Haren, Oliver Gruber, Patrick D. McGorry, G. Paul Amminger, Philip McGuire, Qiyong Gong, René S. Kahn, Rosa Ayesa‐Arriola, Thérèse van Amelsvoort, Víctor Ortiz‐García de la Foz, Vince D. Calhoun, Wiepke Cahn, Andrea Mechelli

2020NeuroImage90 citationsDOIOpen Access PDF

Abstract

• We present Neuroharmony, a harmonization tool for images from unseen scanners. • We developed Neuroharmony using a total of 15,026 sMRI images. • The tool was able to reduce scanner-related bias from unseen scans. • Neuroharmony represents a significant step towards imaging-based clinical tools. • Neuroharmony is available at https://github.com/garciadias/Neuroharmony .

Topics & Concepts

ScannerComputer scienceArtificial intelligenceHarmonizationComputer visionPhysicsAcousticsAdvanced MRI Techniques and ApplicationsAdvanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity Studies