Automated brain extraction of multisequence MRI using artificial neural networks.


Journal

Human brain mapping
ISSN: 1097-0193
Titre abrégé: Hum Brain Mapp
Pays: United States
ID NLM: 9419065

Informations de publication

Date de publication:
01 12 2019
Historique:
received: 10 12 2018
revised: 19 07 2019
accepted: 23 07 2019
pubmed: 14 8 2019
medline: 17 4 2020
entrez: 13 8 2019
Statut: ppublish

Résumé

Brain extraction is a critical preprocessing step in the analysis of neuroimaging studies conducted with magnetic resonance imaging (MRI) and influences the accuracy of downstream analyses. The majority of brain extraction algorithms are, however, optimized for processing healthy brains and thus frequently fail in the presence of pathologically altered brain or when applied to heterogeneous MRI datasets. Here we introduce a new, rigorously validated algorithm (termed HD-BET) relying on artificial neural networks that aim to overcome these limitations. We demonstrate that HD-BET outperforms six popular, publicly available brain extraction algorithms in several large-scale neuroimaging datasets, including one from a prospective multicentric trial in neuro-oncology, yielding state-of-the-art performance with median improvements of +1.16 to +2.50 points for the Dice coefficient and -0.66 to -2.51 mm for the Hausdorff distance. Importantly, the HD-BET algorithm, which shows robust performance in the presence of pathology or treatment-induced tissue alterations, is applicable to a broad range of MRI sequence types and is not influenced by variations in MRI hardware and acquisition parameters encountered in both research and clinical practice. For broader accessibility, the HD-BET prediction algorithm is made freely available (www.neuroAI-HD.org) and may become an essential component for robust, automated, high-throughput processing of MRI neuroimaging data.

Identifiants

pubmed: 31403237
doi: 10.1002/hbm.24750
pmc: PMC6865732
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

4952-4964

Subventions

Organisme : Else Kröner-Fresenius Foundation
Pays : International
Organisme : Medical Faculty Heidelberg Postdoc-Program
Pays : International

Informations de copyright

© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.

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Auteurs

Fabian Isensee (F)

Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Faculty of Biosciences, University of Heidelberg, Heidelberg, Germany.

Marianne Schell (M)

Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.

Irada Pflueger (I)

Department of Radiology, DKFZ, Heidelberg, Germany.

Gianluca Brugnara (G)

Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.

David Bonekamp (D)

Department of Radiology, DKFZ, Heidelberg, Germany.

Ulf Neuberger (U)

Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.

Antje Wick (A)

Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany.

Heinz-Peter Schlemmer (HP)

Department of Radiology, DKFZ, Heidelberg, Germany.

Sabine Heiland (S)

Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.

Wolfgang Wick (W)

Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany.
German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany.

Martin Bendszus (M)

Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.

Klaus H Maier-Hein (KH)

Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany.

Philipp Kickingereder (P)

Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.

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