GRASPNET: Fast spatiotemporal deep learning reconstruction of golden‐angle radial data for free‐breathing dynamic contrast‐enhanced magnetic resonance imaging

The purpose of the current study was to develop a deep learning technique called Golden‐angle RAdial Sparse Parallel Network (GRASPnet) for fast reconstruction of dynamic contrast‐enhanced 4D MRI acquired with golden‐angle radial k‐space trajectories. GRASPnet operates in the image‐time space and do...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	NMR in biomedicine 2023-03, Vol.36 (3), p.e4861-n/a
Hauptverfasser:	Jafari, Ramin, Do, Richard Kinh Gian, LaGratta, Maria Divina, Fung, Maggie, Bayram, Ersin, Cashen, Ty, Otazo, Ricardo
Format:	Artikel
Sprache:	eng
Schlagworte:	Biological products Computer architecture Contrast Media Deep Learning dynamic contrast‐enhanced MRI free breathing golden angle Humans Image contrast Image enhancement Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image reconstruction Imaging, Three-Dimensional - methods Kernels Magnetic resonance imaging Magnetic Resonance Imaging - methods Medical imaging Qualitative analysis Quantitative analysis radial Respiration
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!