title: Application of 3D-MR image registration to monitor diseases around the knee joint.
abstract: OBJECTIVE
  To estimate the accuracy and consistency of a method using a voxel-based MR image registration algorithm for precise monitoring of knee joint diseases.
  
  
  METHODS
  Rigid body transformation was calculated using a normalized cross-correlation (NCC) algorithm involving simple manual segmentation of the bone region based on its anatomical features. The accuracy of registration was evaluated using four phantoms, followed by a consistency test using MR data from the 11 patients with knee joint disease.
  
  
  RESULTS
  The registration accuracy in the phantom experiment was 0.49+/-0.19 mm (SD) for the femur and 0.56+/-0.21 mm (SD) for the tibia. The consistency value in the experiment using clinical data was 0.69+/-0.25 mm (SD) for the femur and 0.77+/-0.37 mm (SD) for the tibia. These values were all smaller than a voxel (1.25 x 1.25 x 1.5 mm).
  
  
  CONCLUSIONS
  The present method based on an NCC algorithm can be used to register serial MR images of the knee joint with error on the order of a sub-voxel. This method would be useful for precisely assessing therapeutic response and monitoring knee joint diseases; normalized cross-correlation; accuracy.
authors.affiliation: Department of Orthopedic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan. masaki-tko@umin.ac.jp
authors.forename: Masaki
authors.initials: M
authors.lastname: Takao
authors.forename: Nobuhiko
authors.initials: N
authors.lastname: Sugano
authors.forename: Takashi
authors.initials: T
authors.lastname: Nishii
authors.forename: Hidenobu
authors.initials: H
authors.lastname: Miki
authors.forename: Tsuyoshi
authors.initials: T
authors.lastname: Koyama
authors.forename: Jun
authors.initials: J
authors.lastname: Masumoto
authors.forename: Yoshinobu
authors.initials: Y
authors.lastname: Sato
authors.forename: Shinichi
authors.initials: S
authors.lastname: Tamura
authors.forename: Hideki
authors.initials: H
authors.lastname: Yoshikawa
mesh_terms: D000465:Algorithms; D005269:Femur / Q000473:pathology; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007719:Knee Joint / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010020:Osteonecrosis / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D013977:Tibia / Q000473:pathology