title: Inferring 3D kinematics of carpal bones from single view fluoroscopic sequences.
abstract: We present a novel framework for inferring 3D carpal bone kinematics and bone shapes from a single view fluoroscopic sequence. A hybrid statistical model representing both the kinematics and shape variation of the carpal bones is built, based on a number of 3D CT data sets obtained from different subjects at different poses. Given a fluoroscopic sequence, the wrist pose, carpal bone kinematics and bone shapes are estimated iteratively by matching the statistical model with the 2D images. A specially designed cost function enables smoothed parameter estimation across frames. We have evaluated the proposed method on both simulated data and real fluoroscopic sequences. It was found that the relative positions between carpal bones can be accurately estimated, which is potentially useful for detection of conditions such as scapholunate dissociation.
authors: ISBE, School of Cancer and Enabling Sciences, University of Manchester, Oxford Road, Manchester M13 9PT, UK. xin.chen@manchester.ac.uk
authors: Xin
authors: X
authors: Chen
authors: Jim
authors: J
authors: Graham
authors: Charles
authors: C
authors: Hutchinson
authors: Lindsay
authors: L
authors: Muir
mesh_terms: D000465:Algorithms; D001696:Biomechanical Phenomena; D002348:Carpal Bones / Q000000981:diagnostic imaging / Q000473:pathology*; D003198:Computer Simulation; D003952:Diagnostic Imaging / Q000379:methods*; D005471:Fluoroscopy / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods*; D015233:Models, Statistical; D011884:Radius / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014457:Ulna / Q000000981:diagnostic imaging