title: Fluoroscopy-based tracking of femoral kinematics with statistical shape models.
abstract: OBJECTIVE
  Precise knee kinematics assessment helps to diagnose knee pathologies and to improve the design of customized prosthetic components. The first step in identifying knee kinematics is to assess the femoral motion in the anatomical frame. However, no work has been done on pathological femurs, whose shape can be highly different from healthy ones.
  
  
  METHODS
  We propose a new femoral tracking technique based on statistical shape models and two calibrated fluoroscopic images, taken at different flexion-extension angles. The cost function optimization is based on genetic algorithms, to avoid local minima. The proposed approach was evaluated on 3 sets of digitally reconstructed radiographic images of osteoarthritic patients.
  
  
  RESULTS
  It is found that using the estimated shape, rather than that calculated from CT, significantly reduces the pose accuracy, but still has reasonably good results (angle errors around 2[Formula: see text], translation around 1.5 mm).
authors.affiliation: Department of Electronics, Information and Bioengineering, Politecnico di Milano, Via Colombo 40, 20133, Milan, Italy. marta.valenti@polimi.it.
authors.forename: Marta
authors.initials: M
authors.lastname: Valenti
authors.affiliation: Department of Electronics, Information and Bioengineering, Politecnico di Milano, Via Colombo 40, 20133, Milan, Italy.
authors.forename: Elena
authors.initials: E
authors.lastname: De Momi
authors.affiliation: Universität Bern, Staffaucherstr. 78, 3014, Bern, Switzerland.
authors.forename: Weimin
authors.initials: W
authors.lastname: Yu
authors.affiliation: Department of Electronics, Information and Bioengineering, Politecnico di Milano, Via Colombo 40, 20133, Milan, Italy.
authors.forename: Giancarlo
authors.initials: G
authors.lastname: Ferrigno
authors.affiliation: University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada.
authors.forename: Mohsen
authors.initials: M
authors.lastname: Akbari Shandiz
authors.affiliation: University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada.
authors.forename: Carolyn
authors.initials: C
authors.lastname: Anglin
authors.affiliation: Universität Bern, Staffaucherstr. 78, 3014, Bern, Switzerland.
authors.forename: Guoyan
authors.initials: G
authors.lastname: Zheng
mesh_terms: D000465:Algorithms; D001696:Biomechanical Phenomena; D005260:Female; D005269:Femur / Q000000981:diagnostic imaging* / Q000503:physiopathology; D005471:Fluoroscopy / Q000379:methods; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007595:Joint Prosthesis; D007719:Knee Joint / Q000000981:diagnostic imaging* / Q000503:physiopathology; D015233:Models, Statistical; D020370:Osteoarthritis, Knee / Q000601:surgery*; D011474:Prosthesis Design; D016059:Range of Motion, Articular; D014057:Tomography, X-Ray Computed
keywords: Computer-assisted surgery; Digitally reconstructed radiographs; Image processing; Statistical shape models