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WeightNameValue
1000 Titel
  • High-resolution diffusion MRI at 7T using a three-dimensional multi-slab acquisition
1000 Autor/in
  1. Wu, Wenchuan |
  2. Poser, Benedikt A. |
  3. Douaud, Gwenaëlle |
  4. Frost, Robert |
  5. In, Myung-Ho |
  6. Speck, Oliver |
  7. Koopmans, Peter J. |
  8. Miller, Karla L. |
1000 Erscheinungsjahr 2016
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2016-08-26
1000 Erschienen in
1000 Quellenangabe
  • 143: 1-14
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2016
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1016/j.neuroimage.2016.08.054 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5139985/ |
1000 Ergänzendes Material
  • http://www.sciencedirect.com/science/article/pii/S1053811916304463?via%3Dihub#s0100 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • High-resolution diffusion MRI can provide the ability to resolve small brain structures, enabling investigations of detailed white matter architecture. A major challenge for in vivo high-resolution diffusion MRI is the low signal-to-noise ratio. In this work, we combine two highly compatible methods, ultra-high field and three-dimensional multi-slab acquisition to improve the SNR of high-resolution diffusion MRI. As each kz plane is encoded using a single-shot echo planar readout, scan speeds of the proposed technique are similar to the commonly used two-dimensional diffusion MRI. In-plane parallel acceleration is applied to reduce image distortions. To reduce the sensitivity of auto-calibration signal data to subject motion and respiration, several new adaptions of the fast low angle excitation echo-planar technique (FLEET) that are suitable for 3D multi-slab echo planar imaging are proposed and evaluated. A modified reconstruction scheme is proposed for auto-calibration with the most robust method, Slice-FLEET acquisition, to make it compatible with navigator correction of motion induced phase errors. Slab boundary artefacts are corrected using the nonlinear slab profile encoding method recently proposed by our group. In vivo results demonstrate that using 7T and three-dimensional multi-slab acquisition with improved auto-calibration signal acquisition and nonlinear slab boundary artefacts correction, high-quality diffusion MRI data with ~1 mm isotropic resolution can be achieved.
1000 Sacherschließung
lokal 7T
lokal Diffusion
lokal Tractography
lokal 3D
lokal High resolution
lokal Multi-slab
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/creator/V3UsIFdlbmNodWFu|https://frl.publisso.de/adhoc/creator/UG9zZXIsIEJlbmVkaWt0IEEu|https://frl.publisso.de/adhoc/creator/RG91YXVkLCBHd2VuYcOrbGxl|https://frl.publisso.de/adhoc/creator/RnJvc3QsIFJvYmVydA==|https://frl.publisso.de/adhoc/creator/SW4sIE15dW5nLUhv|http://orcid.org/0000-0002-6019-5597|https://frl.publisso.de/adhoc/creator/S29vcG1hbnMsIFBldGVyIEou|https://frl.publisso.de/adhoc/creator/TWlsbGVyLCBLYXJsYSBMLg==
1000 Label
1000 Förderer
  1. Marie Curie Initial Training Network |
  2. Wellcome Trust |
  3. NIHR Oxford Biomedical Research Centre |
1000 Fördernummer
  1. FP7-PEOPLE-2012-ITN-316716
  2. 091509/Z/10/Z; WT100092MA
  3. -
1000 Förderprogramm
  1. -
  2. -
  3. postdoctoral fellowship
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Marie Curie Initial Training Network |
    1000 Förderprogramm -
    1000 Fördernummer FP7-PEOPLE-2012-ITN-316716
  2. 1000 joinedFunding-child
    1000 Förderer Wellcome Trust |
    1000 Förderprogramm -
    1000 Fördernummer 091509/Z/10/Z; WT100092MA
  3. 1000 joinedFunding-child
    1000 Förderer NIHR Oxford Biomedical Research Centre |
    1000 Förderprogramm postdoctoral fellowship
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6406166.rdf
1000 Erstellt am 2018-01-04T18:20:56.866+0100
1000 Erstellt von 218
1000 beschreibt frl:6406166
1000 Bearbeitet von 288
1000 Zuletzt bearbeitet Wed Mar 31 09:33:43 CEST 2021
1000 Objekt bearb. Wed Mar 31 09:33:43 CEST 2021
1000 Vgl. frl:6406166
1000 Oai Id
  1. oai:frl.publisso.de:frl:6406166 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

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