Graphical Modeling of Ultrasound Propagation in Tissue for Automatic Bone Segmentation

  • Firat OzdemirEmail author
  • Ece Ozkan
  • Orcun Goksel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9901)


Bone surface identification and localization in ultrasound have been widely studied in the contexts of computer-assisted orthopedic surgeries, trauma diagnosis, and post-operative follow-up. Nevertheless, the (semi-)automatic bone surface segmentation methods proposed so far either require manual interaction or complex parametrizations, while failing to deliver accuracy fit for clinical purposes. In this paper, we utilize the physics of ultrasound propagation in human tissue by encoding this in a factor graph formulation for an automatic bone surface segmentation approach. We comparatively evaluate our method on annotated in-vivo ultrasound images of bones from several anatomical locations. Our method yields a root-mean-square error of 0.59 mm, far superior to state-of-the-art approaches.


Bone Surface Local Binary Pattern Markov Random Fields Phase Symmetry Factor Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank Dr. Andreas Schweizer for annotations, and to Swiss National Science Foundation and Zurich Department of Health for funding.


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© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Computer-Assisted Applications in MedicineETH ZurichZurichSwitzerland

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