title: Vertebral morphometry: semiautomatic determination of detailed shape from dual-energy X-ray absorptiometry images using active appearance models.
abstract: OBJECTIVE
  Manual point placement for vertebral morphometry is time-consuming and imprecise. We evaluated the accuracy of semiautomatic computer determination of the detailed vertebral shape.
  
  
  METHODS
  The shape and appearance of vertebrae on 250 lateral dual-energy x-ray absorptiometry (DXA) scans were statistically modeled using a sequence of active appearance models of vertebral triplets. The models were matched to unseen scans given an approximate initial location of the center of each vertebra. The segmentation accuracy was analyzed by fracture grade.
  
  
  RESULTS
  Segmentation accuracy comparable to manual precision was obtained in the case of normal vertebrae, but the accuracy decreased with increasing fracture severity. We propose methods for improving the robustness for severe fractures.
  
  
  CONCLUSIONS
  Vertebral morphometry measurements may be substantially automated even on noisy data with multiple fractures present. The shape and appearance parameters of the models could provide more powerful quantitative classifiers of osteoporotic vertebral fracture.
authors.affiliation: Imaging Science and Biomedical Engineering, University of Manchester, Manchester, UK. martin.roberts@manchester.ac.uk
authors.forename: Martin
authors.initials: M
authors.lastname: Roberts
authors.forename: Timothy F
authors.initials: TF
authors.lastname: Cootes
authors.forename: Judith E
authors.initials: JE
authors.lastname: Adams
mesh_terms: D015502:Absorptiometry, Photon; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002574:Cervical Vertebrae / Q000033:anatomy & histology* / Q000000981:diagnostic imaging; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D016103:Spinal Fractures / Q000175:diagnosis*