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

Rafael Garcia-Dias; Cristina Scarpazza; Lea Baecker; Sandra Vieira; Walter H. L. Pinaya; Aiden Corvin; Alberto Redolfi; Barnaby Nelson; Benedicto Crespo-Facorro; Colm McDonald; Diana Tordesillas-Gutierrez; Dara Cannon; David Mothersill; Dennis Hernaus; Derek Morris; Esther Setien-Suero; Gary Donohoe; Giovanni Frisoni; Giulia Tronchin; Joao Sato; Machteld Marcelis; Matthew Kempton; Neeltje E. M. van Haren; Oliver Gruber; Patrick McGorry; Paul Amminger; Philip McGuire; Qiyong Gong; Rene S. Kahn; Rosa Ayesa-Arriola; Therese van Amelsvoort; Victor Ortiz-Garcia de la Foz; Vince Calhoun; Wiepke Cahn; Andrea Mechelli

doi:10.1016/j.neuroimage.2020.117127

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

Rafael Garcia-Dias^*, Cristina Scarpazza, Lea Baecker, Sandra Vieira, Walter H. L. Pinaya, Aiden Corvin, Alberto Redolfi, Barnaby Nelson, Benedicto Crespo-Facorro, Colm McDonald, Diana Tordesillas-Gutierrez, Dara Cannon, David Mothersill, Dennis Hernaus, Derek Morris, Esther Setien-Suero, Gary Donohoe, Giovanni Frisoni, Giulia Tronchin, Joao SatoMachteld Marcelis, Matthew Kempton, Neeltje E. M. van Haren, Oliver Gruber, Patrick McGorry, Paul Amminger, Philip McGuire, Qiyong Gong, Rene S. Kahn, Rosa Ayesa-Arriola, Therese van Amelsvoort, Victor Ortiz-Garcia de la Foz, Vince Calhoun, Wiepke Cahn, Andrea Mechelli

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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.

Original language	English
Article number	117127
Number of pages	15
Journal	Neuroimage
Volume	220
DOIs	https://doi.org/10.1016/j.neuroimage.2020.117127
Publication status	Published - 15 Oct 2020

Keywords

VOXEL-BASED MORPHOMETRY
FALSE-POSITIVE RATES
ALZHEIMERS-DISEASE
CORTICAL THICKNESS
SINGLE MATTERS
BRAIN
CLASSIFICATION
MACHINE
IMAGES
SEGMENTATION

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Cite this

Garcia-Dias, R., Scarpazza, C., Baecker, L., Vieira, S., Pinaya, W. H. L., Corvin, A., Redolfi, A., Nelson, B., Crespo-Facorro, B., McDonald, C., Tordesillas-Gutierrez, D., Cannon, D., Mothersill, D., Hernaus, D., Morris, D., Setien-Suero, E., Donohoe, G., Frisoni, G., Tronchin, G., ... Mechelli, A. (2020). Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners. Neuroimage, 220, Article 117127. https://doi.org/10.1016/j.neuroimage.2020.117127

@article{43e802edb5a34a75b2b8278a86bd0b09,

title = "Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners",

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.",

keywords = "VOXEL-BASED MORPHOMETRY, FALSE-POSITIVE RATES, ALZHEIMERS-DISEASE, CORTICAL THICKNESS, SINGLE MATTERS, BRAIN, CLASSIFICATION, MACHINE, IMAGES, SEGMENTATION",

author = "Rafael Garcia-Dias and Cristina Scarpazza and Lea Baecker and Sandra Vieira and Pinaya, {Walter H. L.} and Aiden Corvin and Alberto Redolfi and Barnaby Nelson and Benedicto Crespo-Facorro and Colm McDonald and Diana Tordesillas-Gutierrez and Dara Cannon and David Mothersill and Dennis Hernaus and Derek Morris and Esther Setien-Suero and Gary Donohoe and Giovanni Frisoni and Giulia Tronchin and Joao Sato and Machteld Marcelis and Matthew Kempton and {van Haren}, {Neeltje E. M.} and Oliver Gruber and Patrick McGorry and Paul Amminger and Philip McGuire and Qiyong Gong and Kahn, {Rene S.} and Rosa Ayesa-Arriola and {van Amelsvoort}, Therese and {de la Foz}, {Victor Ortiz-Garcia} and Vince Calhoun and Wiepke Cahn and Andrea Mechelli",

year = "2020",

month = oct,

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doi = "10.1016/j.neuroimage.2020.117127",

language = "English",

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Garcia-Dias, R, Scarpazza, C, Baecker, L, Vieira, S, Pinaya, WHL, Corvin, A, Redolfi, A, Nelson, B, Crespo-Facorro, B, McDonald, C, Tordesillas-Gutierrez, D, Cannon, D, Mothersill, D, Hernaus, D, Morris, D, Setien-Suero, E, Donohoe, G, Frisoni, G, Tronchin, G, Sato, J, Marcelis, M, Kempton, M, van Haren, NEM, Gruber, O, McGorry, P, Amminger, P, McGuire, P, Gong, Q, Kahn, RS, Ayesa-Arriola, R, van Amelsvoort, T, de la Foz, VO-G, Calhoun, V, Cahn, W & Mechelli, A 2020, 'Neuroharmony: A new tool for harmonizing volumetric MRI data from unseen scanners', Neuroimage, vol. 220, 117127. https://doi.org/10.1016/j.neuroimage.2020.117127

TY - JOUR

T1 - Neuroharmony

T2 - A new tool for harmonizing volumetric MRI data from unseen scanners

AU - Garcia-Dias, Rafael

AU - Scarpazza, Cristina

AU - Baecker, Lea

AU - Vieira, Sandra

AU - Pinaya, Walter H. L.

AU - Corvin, Aiden

AU - Redolfi, Alberto

AU - Nelson, Barnaby

AU - Crespo-Facorro, Benedicto

AU - McDonald, Colm

AU - Tordesillas-Gutierrez, Diana

AU - Cannon, Dara

AU - Mothersill, David

AU - Hernaus, Dennis

AU - Morris, Derek

AU - Setien-Suero, Esther

AU - Donohoe, Gary

AU - Frisoni, Giovanni

AU - Tronchin, Giulia

AU - Sato, Joao

AU - Marcelis, Machteld

AU - Kempton, Matthew

AU - van Haren, Neeltje E. M.

AU - Gruber, Oliver

AU - McGorry, Patrick

AU - Amminger, Paul

AU - McGuire, Philip

AU - Gong, Qiyong

AU - Kahn, Rene S.

AU - Ayesa-Arriola, Rosa

AU - van Amelsvoort, Therese

AU - de la Foz, Victor Ortiz-Garcia

AU - Calhoun, Vince

AU - Cahn, Wiepke

AU - Mechelli, Andrea

PY - 2020/10/15

Y1 - 2020/10/15

N2 - • 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.

AB - • 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.

KW - VOXEL-BASED MORPHOMETRY

KW - FALSE-POSITIVE RATES

KW - ALZHEIMERS-DISEASE

KW - CORTICAL THICKNESS

KW - SINGLE MATTERS

KW - BRAIN

KW - CLASSIFICATION

KW - MACHINE

KW - IMAGES

KW - SEGMENTATION

U2 - 10.1016/j.neuroimage.2020.117127

DO - 10.1016/j.neuroimage.2020.117127

M3 - Article

C2 - 32634595

SN - 1053-8119

VL - 220

JO - Neuroimage

JF - Neuroimage

M1 - 117127

ER -