Automatic detection of vertebral number abnormalities in body CT images

  • Shouhei HanaokaEmail author
  • Yoshiyasu Nakano
  • Mitsutaka Nemoto
  • Yukihiro Nomura
  • Tomomi Takenaga
  • Soichiro Miki
  • Takeharu Yoshikawa
  • Naoto Hayashi
  • Yoshitaka Masutani
  • Akinobu Shimizu
Original Article



The anatomical anomaly of the number of vertebral bones is one of the major anomalies in the human body, which can cause confusion of the spinal level in, for example, surgery. The aim of this study is to develop an automatic detection system for this type of anomaly.


We utilized our previously reported anatomical landmark detection system for this anomaly detection problem. This system uses a landmark point distribution model (L-PDM) to find multiple landmark positions. The L-PDM is a statistical probabilistic model of all landmark positions in the human body, including five landmarks for each vertebra. Given a new volume, the proposed algorithm applies five hypotheses (normal, 11 or 13 thoracic vertebrae, 4 or 6 lumbar vertebrae) to the given spine and attempts to detect all the landmarks. Then, the most plausible hypothesis with the largest posterior likelihood is selected as the anatomy detection result.


The proposed method was evaluated using 300 neck-to-pelvis CT datasets. For normal subjects, the vertebrae of 211/217 (97.2%) of the subjects were successfully determined as normal. For subjects with 23 or 25 vertebrae without a transitional vertebra (TV), the vertebrae of 9/10 (90%) of the subjects were successfully determined. For subjects with TV, the vertebrae of 71/73 (97.3%) of subjects were judged as partially successfully determined.


Our algorithm successfully determined the number of vertebrae, and the feasibility of our proposed system was validated.


Anatomical anomaly Anatomical landmark Spine Computed tomography 



This work was supported in part by JSPS Grants-in-Aid for Scientific Research KAKENHI Grant Numbers 15H01108 and 15K19775.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1975 Helsinki Declaration, as revised in 2008(5). For this type of study, formal consent is not required.


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Copyright information

© CARS 2017

Authors and Affiliations

  • Shouhei Hanaoka
    • 1
    • 2
    Email author
  • Yoshiyasu Nakano
    • 1
  • Mitsutaka Nemoto
    • 3
  • Yukihiro Nomura
    • 3
  • Tomomi Takenaga
    • 3
  • Soichiro Miki
    • 3
  • Takeharu Yoshikawa
    • 3
  • Naoto Hayashi
    • 3
  • Yoshitaka Masutani
    • 4
  • Akinobu Shimizu
    • 2
  1. 1.Department of RadiologyThe University of Tokyo HospitalBunkyo-ku, TokyoJapan
  2. 2.Institute of EngineeringTokyo University of Agriculture and TechnologyTokyoJapan
  3. 3.Department of Computational Diagnostic Radiology and Preventive MedicineThe University of Tokyo HospitalTokyoJapan
  4. 4.Department of Intelligent Systems, Graduate School of Information SciencesHiroshima City UniversityHiroshimaJapan

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