title: Validation of a hybrid Doppler ultrasound vessel-based registration algorithm for neurosurgery.
abstract: OBJECTIVE
  We describe and validate a novel hybrid nonlinear vessel registration algorithm for intra-operative updating of preoperative magnetic resonance (MR) images using Doppler ultrasound (US) images acquired on the dura for the correction of brain-shift and registration inaccuracies. We also introduce an US vessel appearance simulator that generates vessel images similar in appearance to that acquired with US from MR angiography data.
  
  
  METHODS
  Our registration uses the minimum amount of preprocessing to extract vessels from the raw volumetric images. This prevents the removal of important registration information and minimizes the introduction of artifacts that may affect robustness, while reducing the amount of extraneous information in the image to be processed, thus improving the convergence speed of the algorithm. We then completed 3 rounds of validation for our vessel registration method for robustness and accuracy using (i) a large number of synthetic trials generated with our US vessel simulator, (ii) US images acquired from a real physical phantom made from polyvinyl alcohol cryogel, and (iii) real clinical data gathered intra-operatively from 3 patients.
  
  
  RESULTS
  Resulting target registration errors (TRE) of less than 2.5 mm are achieved in more than 90 % of the synthetic trials when the initial TREs are less than 20 mm. TREs of less than 2 mm were achieved when the technique was applied to the physical phantom, and TREs of less than 3 mm were achieved on clinical data.
  
  
  CONCLUSIONS
  These test trials show that the proposed algorithm is not only accurate but also highly robust to noise and missing vessel segments when working with US images acquired in a wide range of real-world conditions.
authors.affiliation: McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada. sjschen@bic.mni.mcgill.ca
authors.forename: Sean Jy-Shyang
authors.initials: SJ
authors.lastname: Chen
authors.forename: Ingerid
authors.initials: I
authors.lastname: Reinertsen
authors.forename: Pierrick
authors.initials: P
authors.lastname: Coupé
authors.forename: Charles X B
authors.initials: CX
authors.lastname: Yan
authors.forename: Laurence
authors.initials: L
authors.lastname: Mercier
authors.forename: D Rolando
authors.initials: DR
authors.lastname: Del Maestro
authors.forename: D Louis
authors.initials: DL
authors.lastname: Collins
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001921:Brain / Q000098:blood supply / Q000601:surgery; D005260:Female; D006801:Humans; D007432:Intraoperative Period; D018810:Magnetic Resonance Angiography; D008297:Male; D008875:Middle Aged; D038361:Neuronavigation / Q000379:methods*; D019635:Neurosurgical Procedures; D019047:Phantoms, Imaging; D057234:Preoperative Period; D018608:Ultrasonography, Doppler