Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
  Investigating complex-valued neural networks applied to phase-cycled bSSFP for multi-parametric quantitative tissue characterization

Birk, F., Steiglechner, J., Scheffler, K., & Heule, R. (2022). Investigating complex-valued neural networks applied to phase-cycled bSSFP for multi-parametric quantitative tissue characterization. Poster presented at Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting (ISMRM 2022), London, UK.

Item is

Externe Referenzen

einblenden:
ausblenden:
externe Referenz:
https://archive.ismrm.org/2022/2532.html (Zusammenfassung)
Beschreibung:
-
OA-Status:
Keine Angabe

Urheber

einblenden:
ausblenden:
 Urheber:
Birk, F1, Autor           
Steiglechner, J1, Autor           
Scheffler, K1, Autor           
Heule, R1, Autor           
Affiliations:
1Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              

Inhalt

einblenden:
ausblenden:
Schlagwörter: -
 Zusammenfassung: The bSSFP sequence is highly sensitive to relaxation parameters, tissue microstructure, and off-resonance frequencies, which has recently been shown to enable multi-parametric tissue characterization in the human brain using real-valued NNs. In this work, a new approach based on complex-valued NNs for voxel-wise simultaneous multi-parametric quantitative mapping with phase-cycled bSSFP input data is presented, possibly facilitating data handling. Relaxometry parameters (T1, T2) and field map estimates (B1+, ΔB0) could be quantified with high robustness and accuracy. The quantitative results were compared for different activation functions, favoring phase-sensitive implementations.

Details

einblenden:
ausblenden:
Sprache(n):
 Datum: 2022-05
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: -
 Art des Abschluß: -

Veranstaltung

einblenden:
ausblenden:
Titel: Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting (ISMRM 2022)
Veranstaltungsort: London, UK
Start-/Enddatum: 2022-05-07 - 2022-05-12

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting (ISMRM 2022)
Genre der Quelle: Konferenzband
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: - Artikelnummer: 2532 Start- / Endseite: - Identifikator: -