DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping

Steffen Bollmann, Kasper Gade Bøtker Rasmussen, Mads Kristensen, Rasmus Guldhammer Blendal, Lasse Riis Østergaard, Maciej Plocharski, Kieran O'Brien, Christian Langkammer, Andrew Janke, Markus Barth

Research output: Contribution to journalJournal articleResearchpeer-review

Original languageEnglish
JournalNeuroImage
Volume195
Pages (from-to)373-383
Number of pages11
ISSN1053-8119
DOIs
Publication statusPublished - Jul 2019

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Bibliographical note

Copyright © 2019 Elsevier Inc. All rights reserved.

Keywords

  • Deep learning
  • Dipole inversion
  • Ill-posed problem
  • Quantitative susceptibility mapping

Cite this

Bollmann, Steffen ; Rasmussen, Kasper Gade Bøtker ; Kristensen, Mads ; Blendal, Rasmus Guldhammer ; Østergaard, Lasse Riis ; Plocharski, Maciej ; O'Brien, Kieran ; Langkammer, Christian ; Janke, Andrew ; Barth, Markus. / DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping. In: NeuroImage. 2019 ; Vol. 195. pp. 373-383.
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title = "DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping",
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author = "Steffen Bollmann and Rasmussen, {Kasper Gade B{\o}tker} and Mads Kristensen and Blendal, {Rasmus Guldhammer} and {\O}stergaard, {Lasse Riis} and Maciej Plocharski and Kieran O'Brien and Christian Langkammer and Andrew Janke and Markus Barth",
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year = "2019",
month = "7",
doi = "10.1016/j.neuroimage.2019.03.060",
language = "English",
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Bollmann, S, Rasmussen, KGB, Kristensen, M, Blendal, RG, Østergaard, LR, Plocharski, M, O'Brien, K, Langkammer, C, Janke, A & Barth, M 2019, 'DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping', NeuroImage, vol. 195, pp. 373-383. https://doi.org/10.1016/j.neuroimage.2019.03.060

DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping. / Bollmann, Steffen; Rasmussen, Kasper Gade Bøtker; Kristensen, Mads; Blendal, Rasmus Guldhammer; Østergaard, Lasse Riis; Plocharski, Maciej; O'Brien, Kieran; Langkammer, Christian; Janke, Andrew; Barth, Markus.

In: NeuroImage, Vol. 195, 07.2019, p. 373-383.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping

AU - Bollmann, Steffen

AU - Rasmussen, Kasper Gade Bøtker

AU - Kristensen, Mads

AU - Blendal, Rasmus Guldhammer

AU - Østergaard, Lasse Riis

AU - Plocharski, Maciej

AU - O'Brien, Kieran

AU - Langkammer, Christian

AU - Janke, Andrew

AU - Barth, Markus

N1 - Copyright © 2019 Elsevier Inc. All rights reserved.

PY - 2019/7

Y1 - 2019/7

KW - Deep learning

KW - Dipole inversion

KW - Ill-posed problem

KW - Quantitative susceptibility mapping

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U2 - 10.1016/j.neuroimage.2019.03.060

DO - 10.1016/j.neuroimage.2019.03.060

M3 - Journal article

VL - 195

SP - 373

EP - 383

JO - NeuroImage

JF - NeuroImage

SN - 1053-8119

ER -