Automatic Segmentation of Bones from 3D Patient Scans

Jim Thompson, Ph.D, Director of Business Development at Siemens PLM Software introduces Siemens image to implant process and how to automate manufacturing of patient-specific medical devices.

Presenting Image-to-Implant segmentation at the American Academy of Orthopaedic Surgeons (AAOS) annual meeting in Chicago, IL. The AAOS annual meeting is among the largest medical meetings in the US with attendance exceeding 30,000.

1. Wu, D., Sofka, M., Birkbeck, N., Zhou, S.K., 2014. Segmentation of Multiple Knee Bones from CT for Orthopedic Knee Surgery Planning. In: Proceedings of the 17th International Conference On Medical Image Computing and Computer-Assisted Intervention (MICCAI 2014). Boston, MA, USA.
   abstract bibtex

   Patient-specific orthopedic knee surgery planning requires precisely segmenting from 3D CT images multiple knee bones, namely femur, tibia, fibula, and patella, around the knee joint with severe pathologies. In this work, we propose a fully automated, highly precise, and computationally efficient joint segmentation approach for multiple bones. First, each bone is initially segmented using a model-based marginal space learning framework for pose estimation followed by non-rigid boundary deformation. To recover shape details, we refine the bone segmentation using the shape priors derived from the initial segmentation and formulate the spatial exclusion constraints between neighboring bones as a multiple layered graph partition problem. As a result, the segmentation accuracy is effectively improved and potential overlap removed. In experimental, we achieve simultaneous segmentation of femur, tibia, patella, and fibula with an overall accuracy of less than 1mm surface-to-surface error in less than 90s on hundreds of 3D CT data sets.

   @inproceedings{wu:miccai14,
     author = {Wu, Dijia and Sofka, Michal and Birkbeck, Neil and Zhou, S.~Kevin},
     title = {Segmentation of Multiple Knee Bones from {CT} for Orthopedic Knee Surgery Planning},
     booktitle = {Proceedings of the 17th International Conference on
                       Medical Image Computing and Computer-Assisted
                       Intervention (MICCAI 2014)},
     year = {2014},
     month = "14--18~" # sep,
     address = {Boston, MA, USA}
   }