title: Landmark-guided diffeomorphic demons algorithm and its application to automatic segmentation of the whole spine and pelvis in CT images.
abstract: OBJECTIVE
  A fully automatic multiatlas-based method for segmentation of the spine and pelvis in a torso CT volume is proposed. A novel landmark-guided diffeomorphic demons algorithm is used to register a given CT image to multiple atlas volumes. This algorithm can utilize both grayscale image information and given landmark coordinate information optimally.
  
  
  METHODS
  The segmentation has four steps. Firstly, 170 bony landmarks are detected in the given volume. Using these landmark positions, an atlas selection procedure is performed to reduce the computational cost of the following registration. Then the chosen atlas volumes are registered to the given CT image. Finally, voxelwise label voting is performed to determine the final segmentation result.
  
  
  RESULTS
  The proposed method was evaluated using 50 torso CT datasets as well as the public SpineWeb dataset. As a result, a mean distance error of [Formula: see text] and a mean Dice coefficient of [Formula: see text] were achieved for the whole spine and the pelvic bones, which are competitive with other state-of-the-art methods.
  
  
  CONCLUSIONS
  From the experimental results, the usefulness of the proposed segmentation method was validated.
authors.affiliation: Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan. hanaoka-tky@umin.ac.jp.|Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo, Japan. hanaoka-tky@umin.ac.jp.
authors.forename: Shouhei
authors.identifier: http://orcid.org/0000-0002-7496-1651
authors.initials: S
authors.lastname: Hanaoka
authors.affiliation: Department of Biomedical Information Sciences, Hiroshima City University, Hiroshima, Japan.
authors.forename: Yoshitaka
authors.initials: Y
authors.lastname: Masutani
authors.affiliation: Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, Tokyo, Japan.
authors.forename: Mitsutaka
authors.initials: M
authors.lastname: Nemoto
authors.affiliation: Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, Tokyo, Japan.
authors.forename: Yukihiro
authors.initials: Y
authors.lastname: Nomura
authors.affiliation: Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, Tokyo, Japan.
authors.forename: Soichiro
authors.initials: S
authors.lastname: Miki
authors.affiliation: Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, Tokyo, Japan.
authors.forename: Takeharu
authors.initials: T
authors.lastname: Yoshikawa
authors.affiliation: Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, Tokyo, Japan.
authors.forename: Naoto
authors.initials: N
authors.lastname: Hayashi
authors.affiliation: Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
authors.forename: Kuni
authors.initials: K
authors.lastname: Ohtomo
authors.affiliation: Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo, Japan.
authors.forename: Akinobu
authors.initials: A
authors.lastname: Shimizu
mesh_terms: D000465:Algorithms; D059925:Anatomic Landmarks / Q000000981:diagnostic imaging*; D054893:Cone-Beam Computed Tomography; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010384:Pelvic Bones / Q000000981:diagnostic imaging*; D013131:Spine / Q000000981:diagnostic imaging*
keywords: Anatomical landmark; Diffeomorphic demons algorithm; Multiatlas segmentation; Pelvis; Spine