BMC Medical Imaging (Sep 2023)

Unsupervised registration of 3D knee implant components to biplanar X-ray images

  • Dac Cong Tai Nguyen,
  • Said Benameur,
  • Max Mignotte,
  • Frédéric Lavoie

DOI
https://doi.org/10.1186/s12880-023-01048-9
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 11

Abstract

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Abstract Background Registration of three-dimensional (3D) knee implant components to radiographic images provides the 3D position of the implants which aids to analyze the component alignment after total knee arthroplasty. Methods We present an automatic 3D to two-dimensional (2D) registration using biplanar radiographic images based on a hybrid similarity measure integrating region and edge-based information. More precisely, this measure is herein defined as a weighted combination of an edge potential field-based similarity, which represents the relation between the external contours of the component projections and an edge potential field estimated on the two radiographic images, and an object specificity property, which is based on the distinction of the region-label inside and outside of the object. Results The accuracy of our 3D/2D registration algorithm was assessed on a sample of 64 components (32 femoral components and 32 tibial components). In our tests, we obtained an average of the root mean square error (RMSE) of 0.18 mm, which is significantly lower than that of both single similarity methods, supporting our hypothesis of better stability and accuracy with the proposed approach. Conclusion Our method, which provides six accurate registration parameters (three rotations and three translations) without requiring any fiducial markers, makes it possible to perform the important analyses on the rotational alignment of the femoral and tibial components on a large number of cases. In addition, this method can be extended to register other implants or bones.

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