title: Fully automatic X-ray image segmentation via joint estimation of image displacements.
abstract: We propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. Our algorithm works by estimating the displacements from image patches to the (unknown) landmark positions and then integrating them via voting. The fundamental contribution is that, we jointly estimate the displacements from all patches to multiple landmarks together, by considering not only the training data but also geometric constraints on the test image. The various constraints constitute a convex objective function that can be solved efficiently. Validated on three challenging datasets, our method achieves high accuracy in landmark detection, and, combined with statistical shape model, gives a better performance in shape segmentation compared to the state-of-the-art methods.
authors: Institute for Surgical Technologies and Biomechanics, Universität Bern, Switzerland.
authors: Cheng
authors: C
authors: Chen
authors: Institute for Surgical Technologies and Biomechanics, Universität Bern, Switzerland.
authors: Weiguo
authors: W
authors: Xie
authors: BG Clinic Ludwigshafen, Ludwigshafen, Germany.
authors: Jochen
authors: J
authors: Franke
authors: BG Clinic Ludwigshafen, Ludwigshafen, Germany.
authors: Paul A
authors: PA
authors: Grützner
authors: Institute for Surgical Technologies and Biomechanics, Universität Bern, Switzerland.
authors: Lutz-P
authors: LP
authors: Nolte
authors: Institute for Surgical Technologies and Biomechanics, Universität Bern, Switzerland.
authors: Guoyan
authors: G
authors: Zheng
mesh_terms: D000465:Algorithms; D059925:Anatomic Landmarks / Q000000981:diagnostic imaging*; D005269:Femur / Q000000981:diagnostic imaging*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D010388:Pelvis / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity