SmartPulse, a machine learning approach for calibration-free dynamic RF shimming: Preliminary study in a clinical environment.

Journal: Magnetic resonance in medicine

PMID: 31257612

Abstract

PURPOSE: A calibration-free pulse design method is introduced to alleviate artifacts in clinical routine with parallel transmission at high field, dealing with significant inter-subject variability, found for instance in the abdomen.

Authors

Raphaël Tomi-Tricot

NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.
Vincent Gras

NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.
Bertrand Thirion

Parietal, Inria, Université Paris-Saclay, Gif-sur-Yvette, France.
Franck Mauconduit

Siemens Healthcare SAS, Saint-Denis, France.
Nicolas Boulant

NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.
Hamza Cherkaoui

Parietal, Inria, Université Paris-Saclay, Gif-sur-Yvette, France.
Pierre Zerbib

Department of Radiology, AP-HP, CHU Henri Mondor, Créteil, France.
Alexandre Vignaud

NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.
Alain Luciani

Medical Imaging Department, Henri Mondor University Hospital, AP-HP, Créteil, France, Inserm, U955, Team 18, 94000 Créteil, France.
Alexis Amadon

NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.

Keywords

Abdomen Adult Aged Aged, 80 and over Algorithms Artifacts Body Mass Index Calibration Cluster Analysis Female Humans Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Machine Learning Magnetic Resonance Imaging Male Middle Aged Radio Waves Reproducibility of Results Young Adult

External Resources

View on PubMed Access via DOI PubMed (31257612)

SmartPulse, a machine learning approach for calibration-free dynamic RF shimming: Preliminary study in a clinical environment.

Abstract

Authors

Keywords

External Resources

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