title: Cortical shell unwrapping for vertebral body abnormality detection on computed tomography.
abstract: The vertebral body is the main axial load-bearing structure of the spinal vertebra. Assessment of acute injury and chronic deformity of the vertebral body is difficult to assess accurately and quantitatively by simple visual inspection. We propose a cortical shell unwrapping method to examine the vertebral body for injury such as fractures and degenerative osteophytes. The spine is first segmented and partitioned into vertebrae. Then the cortical shell of the vertebral body is extracted using deformable dual-surface models. The cortical shell is then unwrapped onto a 2D map and the complex 3D detection problem is effectively converted to a pattern recognition problem on a 2D plane. Characteristic features adapted for different applications are computed and sent to a committee of support vector machines for classification. The system was evaluated on two applications, one for fracture detection on trauma CT datasets and the other on degenerative osteophyte assessment on sodium fluoride PET/CT. The fracture CAD achieved 93.6% sensitivity at 3.2 false positive per patient and the degenerative osteophyte CAD achieved 82% sensitivity at 4.7 false positive per patient.
authors.affiliation: Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, Clinical Center, National Institutes of Health, Bethesda, MD 20892-1182, USA. Electronic address: jyao@cc.nih.gov.
authors.forename: Jianhua
authors.initials: J
authors.lastname: Yao
authors.affiliation: Department of Radiological Sciences, University of California, Irvine, School of Medicine, CA 92868, USA.
authors.forename: Joseph E
authors.initials: JE
authors.lastname: Burns
authors.affiliation: Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, Clinical Center, National Institutes of Health, Bethesda, MD 20892-1182, USA.
authors.forename: Hector
authors.initials: H
authors.lastname: Muñoz
authors.affiliation: Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences Department, Clinical Center, National Institutes of Health, Bethesda, MD 20892-1182, USA.
authors.forename: Ronald M
authors.initials: RM
authors.lastname: Summers
mesh_terms: D000368:Aged; D000465:Algorithms; D001185:Artificial Intelligence; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016103:Spinal Fractures / Q000000981:diagnostic imaging*; D013128:Spinal Osteophytosis / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*
keywords: Computational spine imaging; Computer aided detection