title: Multi-atlas and label fusion approach for patient-specific MRI based skull estimation.
abstract: OBJECTIVE
  MRI-based skull segmentation is a useful procedure for many imaging applications. This study describes a methodology for automatic segmentation of the complete skull from a single T1-weighted volume.
  
  
  METHODS
  The skull is estimated using a multi-atlas segmentation approach. Using a whole head computed tomography (CT) scan database, the skull in a new MRI volume is detected by nonrigid image registration of the volume to every CT, and combination of the individual segmentations by label-fusion. We have compared Majority Voting, Simultaneous Truth and Performance Level Estimation (STAPLE), Shape Based Averaging (SBA), and the Selective and Iterative Method for Performance Level Estimation (SIMPLE) algorithms.
  
  
  RESULTS
  The pipeline has been evaluated quantitatively using images from the Retrospective Image Registration Evaluation database (reaching an overlap of 72.46 ± 6.99%), a clinical CT-MR dataset (maximum overlap of 78.31 ± 6.97%), and a whole head CT-MRI pair (maximum overlap 78.68%). A qualitative evaluation has also been performed on MRI acquisition of volunteers.
  
  
  CONCLUSIONS
  It is possible to automatically segment the complete skull from MRI data using a multi-atlas and label fusion approach. This will allow the creation of complete MRI-based tissue models that can be used in electromagnetic dosimetry applications and attenuation correction in PET/MR.
authors.affiliation: Medical Image Analysis and Biometry Lab, Universidad Rey Juan Carlos, Mostoles, Madrid, Spain.|Madrid-MIT M+Vision Consortium, Madrid, Spain.
authors.forename: Angel
authors.initials: A
authors.lastname: Torrado-Carvajal
authors.affiliation: Madrid-MIT M+Vision Consortium, Madrid, Spain.|Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
authors.forename: Joaquin L
authors.initials: JL
authors.lastname: Herraiz
authors.affiliation: Medical Image Analysis and Biometry Lab, Universidad Rey Juan Carlos, Mostoles, Madrid, Spain.|Madrid-MIT M+Vision Consortium, Madrid, Spain.
authors.forename: Juan A
authors.initials: JA
authors.lastname: Hernandez-Tamames
authors.affiliation: Madrid-MIT M+Vision Consortium, Madrid, Spain.|Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA.
authors.forename: Raul
authors.initials: R
authors.lastname: San Jose-Estepar
authors.affiliation: Madrid-MIT M+Vision Consortium, Madrid, Spain.|Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.|A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.
authors.forename: Yigitcan
authors.initials: Y
authors.lastname: Eryaman
authors.affiliation: MAP5, CNRS UMR 8145, University Paris Descartes, Paris, France.|INRIA Saclay - Ile de France - SELECT, Paris, France.
authors.forename: Yves
authors.initials: Y
authors.lastname: Rozenholc
authors.affiliation: Madrid-MIT M+Vision Consortium, Madrid, Spain.|Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.|Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.|Institute of Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
authors.forename: Elfar
authors.initials: E
authors.lastname: Adalsteinsson
authors.affiliation: A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.|Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
authors.forename: Lawrence L
authors.initials: LL
authors.lastname: Wald
authors.affiliation: Medical Image Analysis and Biometry Lab, Universidad Rey Juan Carlos, Mostoles, Madrid, Spain.|Madrid-MIT M+Vision Consortium, Madrid, Spain.
authors.forename: Norberto
authors.initials: N
authors.lastname: Malpica
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology / Q000000981:diagnostic imaging / Q000473:pathology; D001927:Brain Diseases / Q000000981:diagnostic imaging / Q000473:pathology; D001931:Brain Mapping / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D012886:Skull / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*; D014584:User-Computer Interface; D055815:Young Adult
keywords: MRI; atlas-based; label fusion; skull segmentation; tissue models