A method to reconstruct patient-specific proximal femur surface models from planar pre-operative radiographs

P.E. Galibarov, P.J. Prendergast, A.B. Lennon

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)
5 Downloads (Pure)

Abstract

Three-dimensional reconstruction from volumetric medical images (e.g. CT, MRI) is a well-established technology used in patient-specific modelling. However, there are many cases where only 2D (planar) images may be available, e.g. if radiation dose must be limited or if retrospective data is being used from periods when 3D data was not available. This study aims to address such cases by proposing an automated method to create 3D surface models from planar radiographs. The method consists of (i) contour extraction from the radiograph using an Active Contour (Snake) algorithm, (ii) selection of a closest matching 3D model from a library of generic models, and (iii) warping the selected generic model to improve correlation with the extracted contour.

This method proved to be fully automated, rapid and robust on a given set of radiographs. Measured mean surface distance error values were low when comparing models reconstructed from matching pairs of CT scans and planar X-rays (2.57–3.74 mm) and within ranges of similar studies. Benefits of the method are that it requires a single radiographic image to perform the surface reconstruction task and it is fully automated. Mechanical simulations of loaded bone with different levels of reconstruction accuracy showed that an error in predicted strain fields grows proportionally to the error level in geometric precision. In conclusion, models generated by the proposed technique are deemed acceptable to perform realistic patient-specific simulations when 3D data sources are unavailable.
Original languageEnglish
Pages (from-to)1180-1188
Number of pages9
JournalMedical Engineering and Physics
Volume32
Issue number10
DOIs
Publication statusPublished - Dec 2010

ASJC Scopus subject areas

  • Biomedical Engineering
  • Biophysics

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