title: Automatic detection of over 100 anatomical landmarks in medical CT images: A framework with independent detectors and combinatorial optimization.
abstract: An automatic detection method for 197 anatomically defined landmarks in computed tomography (CT) volumes is presented. The proposed method can handle missed landmarks caused by detection failure, a limited imaging range and other problems using a novel combinatorial optimization framework with a two-stage sampling algorithm. After a list of candidates is generated by each landmark detector, the best combination of candidates is searched for by a combinatorial optimization algorithm using a landmark point distribution model (L-PDM) to provide prior knowledge. Optimization is performed by simulated annealing and iterative Gibbs sampling. Prior to each cycle of Gibbs sampling, another sampling algorithm is processed to estimate the spatial distribution of each target landmark, so that landmark positions without any correct detector-derived candidates can be estimated. The proposed method was evaluated using 104 CT volumes with various imaging ranges. The overall average detection distance error was 6.6mm, and 83.8, 93.2 and 96.5% of landmarks were detected within 10, 15 and 20mm from the ground truth, respectively. The proposed method worked even when most of the landmarks were outside of the imaging range. The identification accuracy of the vertebral centroid was also evaluated using public datasets and the proposed method could identify 70% of vertebrae including severely diseased ones. From these results, the feasibility of our framework in detecting multiple landmarks in various CT datasets was validated.
authors.affiliation: Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, Japan; Tokyo University of Agriculture and Technology, 2-24-16 Nakamachi, Koganei, Tokyo, Japan. Electronic address: hanaoka-tky@umin.ac.jp.
authors.forename: Shouhei
authors.initials: S
authors.lastname: Hanaoka
authors.affiliation: Tokyo University of Agriculture and Technology, 2-24-16 Nakamachi, Koganei, Tokyo, Japan.
authors.forename: Akinobu
authors.initials: A
authors.lastname: Shimizu
authors.affiliation: Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, 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, 7-3-1 Hongo, Bunkyo-ku, 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, 7-3-1 Hongo, Bunkyo-ku, 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, 7-3-1 Hongo, Bunkyo-ku, 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, 7-3-1 Hongo, Bunkyo-ku, 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, Japan.
authors.forename: Kuni
authors.initials: K
authors.lastname: Ohtomo
authors.affiliation: Department of Intelligent Systems, Graduate School of Information Sciences, Hiroshima City University, 3-4-1 Otsuka-higashi, Asaminami-ku, Hiroshima, Japan.
authors.forename: Yoshitaka
authors.initials: Y
authors.lastname: Masutani
mesh_terms: D000465:Algorithms; D059925:Anatomic Landmarks / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013131:Spine / Q000033:anatomy & histology / Q000000981:diagnostic imaging; D013269:Stochastic Processes; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Anatomical landmark; Combinatorial optimization; Computed tomography; Spine