title: PRIMO: Precise radiofrequency inference from multiple observations.
abstract: OBJECTIVE
  This paper presents Precise Radiofrequency Inference from Multiple Observations (PRIMO), a comprehensive reconstruction framework for calibrating MRI systems with parallel transmit and parallel receive radiofrequency capabilities.
  
  
  METHODS
  To date, the vast majority of radiofrequency (RF) calibration methods have considered transmit and receive calibration separately, without acknowledging that transmit field calibration sequences measure sufficient data for receive calibration. PRIMO provides a method of extracting both transmit and receive fields from transmit calibration data without presuming knowledge of either. The method is tested for accuracy through simulation, comparison to a gold standard dataset, and is demonstrated on in-vivo data acquired at 3T.
  
  
  RESULTS
  PRIMO is shown to produce RF fields faithful to the gold standard with errors of less than 3% in realistic noise conditions. The in-vivo reconstructions demonstrate the method's ability to produce high quality transmit and receive maps, with an 8 transmit/8 receive channel system being fully calibrated in three dimensions in approximately 2 minutes.
  
  
  CONCLUSIONS
  PRIMO provides a unified framework for estimating all transmit and receive fields in a single calibration step. This is becoming increasingly relevant in an era of MRI systems with highly parallel RF architectures.
authors.affiliation: King's College London, Division of Imaging Sciences and Biomedical Engineering, The Rayne Institute, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London, UK, SE1 7EH.
authors.forename: Francesco
authors.initials: F
authors.lastname: Padormo
authors.affiliation: King's College London, Division of Imaging Sciences and Biomedical Engineering, The Rayne Institute, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London, UK, SE1 7EH.
authors.forename: Arian
authors.initials: A
authors.lastname: Beqiri
authors.affiliation: King's College London, Division of Imaging Sciences and Biomedical Engineering, The Rayne Institute, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London, UK, SE1 7EH.
authors.forename: Shaihan J
authors.initials: SJ
authors.lastname: Malik
authors.affiliation: King's College London, Division of Imaging Sciences and Biomedical Engineering, The Rayne Institute, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London, UK, SE1 7EH.|King's College London, Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, The Rayne Institute, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London, SE1 7EH, UK.
authors.forename: Joseph V
authors.identifier: http://orcid.org/0000-0002-2690-5495
authors.initials: JV
authors.lastname: Hajnal
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D011846:Radio Waves; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique