title: A Surface-Based Spatial Registration Method Based on Sense Three-Dimensional Scanner.
abstract: OBJECTIVE
  The purpose of this study was to investigate the feasibility of a surface-based registration method based on a low-cost, hand-held Sense three-dimensional (3D) scanner in image-guided neurosurgery system.
  
  
  METHODS
  The scanner was calibrated prior and fixed on a tripod before registration. During registration, a part of the head surface was scanned at first and the spatial position of the adapter was recorded. Then the scanner was taken off from the tripod and the entire head surface was scanned by moving the scanner around the patient's head. All the scan points were aligned to the recorded spatial position to form a unique point cloud of the head by the automatic mosaic function of the scanner. The coordinates of the scan points were transformed from the device space to the adapter space by a calibration matrix, and then to the patient space. A 2-step patient-to-image registration method was then performed to register the patient space to the image space.
  
  
  RESULTS
  The experimental results showed that the mean target registration error of 15 targets on the surface of the phantom was 1.61±0.09 mm. In a clinical experiment, the mean target registration error of 7 targets on the patient's head surface was 2.50±0.31 mm, which was sufficient to meet clinical requirements.
  
  
  CONCLUSIONS
  It is feasible to use the Sense 3D scanner for patient-to-image registration, and the low-cost Sense 3D scanner can take the place of the current used scanner in the image-guided neurosurgery system.
authors.affiliation: *Department of Medical Imaging, HangZhou Medical College, Hangzhou †Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China..
authors.forename: Yifeng
authors.initials: Y
authors.lastname: Fan
authors.forename: Xiufang
authors.initials: X
authors.lastname: Xu
authors.forename: Manning
authors.initials: M
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D002138:Calibration; D005240:Feasibility Studies; D006257:Head / Q000000981:diagnostic imaging*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000295:instrumentation / Q000379:methods*; D019635:Neurosurgical Procedures / Q000295:instrumentation / Q000379:methods*; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000295:instrumentation / Q000379:methods*; D015203:Reproducibility of Results; D025321:Surgery, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*