title: Automated CT segmentation of diseased hip using hierarchical and conditional statistical shape models.
abstract: Segmentation of the femur and pelvis is a prerequisite for patient-specific planning and simulation for hip surgery. Accurate boundary determination of the femoral head and acetabulum is the primary challenge in diseased hip joints because of deformed shapes and extreme narrowness of the joint space. To overcome this difficulty, we investigated a multi-stage method in which the hierarchical hip statistical shape model (SSM) is initially utilized to complete segmentation of the pelvis and distal femur, and then the conditional femoral head SSM is used under the condition that the regions segmented during the previous stage are known. CT data from 100 diseased patients categorized on the basis of their disease type and severity, which included 200 hemi-hips, were used to validate the method, which delivered significantly increased segmentation accuracy for the femoral head.
authors.affiliation: Graduate School of Engineering, Kobe University, Japan.
authors.forename: Futoshi
authors.initials: F
authors.lastname: Yokota
authors.affiliation: Graduate School of Medicine, Osaka University, Japan.
authors.forename: Toshiyuki
authors.initials: T
authors.lastname: Okada
authors.affiliation: Graduate School of Medicine, Osaka University, Japan.
authors.forename: Masaki
authors.initials: M
authors.lastname: Takao
authors.affiliation: Graduate School of Medicine, Osaka University, Japan.
authors.forename: Nobuhiko
authors.initials: N
authors.lastname: Sugano
authors.affiliation: Graduate School of System Informatics, Kobe University, Japan.
authors.forename: Yukio
authors.initials: Y
authors.lastname: Tada
authors.affiliation: Graduate School of Medicine, Osaka University, Japan.
authors.forename: Noriyuki
authors.initials: N
authors.lastname: Tomiyama
authors.affiliation: Graduate School of Medicine, Osaka University, Japan.
authors.forename: Yoshinobu
authors.initials: Y
authors.lastname: Sato
mesh_terms: D000465:Algorithms; D001175:Arthrography / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D015987:Effect Modifier, Epidemiologic; D005260:Female; D006621:Hip Joint / Q000000981:diagnostic imaging* / Q000601:surgery; D006801:Humans; D007592:Joint Diseases / Q000000981:diagnostic imaging*; D008953:Models, Anatomic; D015233:Models, Statistical; 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; D014057:Tomography, X-Ray Computed / Q000379:methods*