title: A new method to validate thoracic CT-CT deformable image registration using auto-segmented 3D anatomical landmarks.
abstract: BACKGROUND
  Deformable image registrations are prone to errors in aligning reliable anatomically features. Consequently, identification of registration inaccuracies is important. Particularly thoracic three-dimensional (3D) computed tomography (CT)-CT image registration is challenging due to lack of contrast in lung tissue. This study aims for validation of thoracic CT-CT image registration using auto-segmented anatomically landmarks.
  
  
  METHODS
  Five lymphoma patients were CT scanned three times within a period of 18 months, with the initial CT defined as the reference scan. For each patient the two successive CT scans were registered to the reference CT using three different image registration algorithms (Demons, B-spline and Affine). The image registrations were evaluated using auto-segmented anatomical landmarks (bronchial branch points) and Dice Similarity Coefficients (DSC). Deviation of corresponding bronchial landmarks were used to quantify inaccuracies in respect of both misalignment and geometric location within lungs.
  
  
  RESULTS
  The median bronchial branch point deviations were 1.6, 1.1 and 4.2 (mm) for the three tested algorithms (Demons, B-spline and Affine). The maximum deviations (> 15 mm) were found within both Demons and B-spline image registrations. In the upper part of the lungs the median deviation of 1.7 (mm) was significantly different (p < 0.02) relative to the median deviations of 2.0 (mm), found in the middle and lower parts of the lungs. The DSC revealed similar registration discrepancies among the three tested algorithms, with DSC values of 0.96, 0.97 and 0.91, for respectively Demons, B-spline and the Affine algorithms.
  
  
  CONCLUSIONS
  Bronchial branch points were found useful to validate thoracic CT-CT image registration. Bronchial branch points identified local registration errors > 15 mm in both Demons and B-spline deformable algorithms.
authors.affiliation: a Department of Medical Physics , Aalborg University Hospital , Denmark.
authors.forename: Martin S
authors.initials: MS
authors.lastname: Nielsen
authors.affiliation: b Department of Health Science and Technology , Aalborg University , Denmark.
authors.forename: Lasse R
authors.initials: LR
authors.lastname: Østergaard
authors.affiliation: a Department of Medical Physics , Aalborg University Hospital , Denmark.
authors.forename: Jesper
authors.initials: J
authors.lastname: Carl
mesh_terms: D000465:Algorithms; D059925:Anatomic Landmarks / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional; D008168:Lung / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement / Q000379:methods; D014057:Tomography, X-Ray Computed