Voxel classification and graph cuts for automated segmentation of pathological periprosthetic hip anatomy

  • Daniel F. Malan
  • Charl P. Botha
  • Edward R. Valstar
Open Access
Original Article

DOI: 10.1007/s11548-012-0671-z

Cite this article as:
Malan, D.F., Botha, C.P. & Valstar, E.R. Int J CARS (2013) 8: 63. doi:10.1007/s11548-012-0671-z

Abstract

Purpose

Automated patient-specific image-based segmentation of tissues surrounding aseptically loose hip prostheses is desired. For this we present an automated segmentation pipeline that labels periprosthetic tissues in computed tomography (CT). The intended application of this pipeline is in pre-operative planning.

Methods

Individual voxels were classified based on a set of automatically extracted image features. Minimum-cost graph cuts were computed on the classification results. The graph-cut step enabled us to enforce geometrical containment constraints, such as cortical bone sheathing the femur’s interior. The solution’s novelty lies in the combination of voxel classification with multilabel graph cuts and in the way label costs were defined to enforce containment constraints.

Results

The segmentation pipeline was tested on a set of twelve manually segmented clinical CT volumes. The distribution of healthy tissue and bone cement was automatically determined with sensitivities greater than 82% and pathological fibrous interface tissue with a sensitivity exceeding 73%. Specificity exceeded 96% for all tissues.

Conclusions

The addition of a graph-cut step improved segmentation compared to voxel classification alone. The pipeline described in this paper represents a practical approach to segmenting multitissue regions from CT.

Keywords

Segmentation Graph cut Voxel classification Osteolysis Computed tomography 

Copyright information

© The Author(s) 2012

Authors and Affiliations

  • Daniel F. Malan
    • 1
    • 2
  • Charl P. Botha
    • 2
    • 3
  • Edward R. Valstar
    • 1
    • 4
  1. 1.Department of OrthopaedicsLeiden University Medical CenterLeidenThe Netherlands
  2. 2.Department of Mediamatics, EEMCSDelft University of TechnologyDelftThe Netherlands
  3. 3.Department of RadiologyLeiden University Medical CenterLeidenThe Netherlands
  4. 4.Department of Biomechanical EngineeringDelft University of TechnologyDelftThe Netherlands

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