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Fully automatic reconstruction of personalized 3D volumes of the proximal femur from 2D X-ray images

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Accurate preoperative planning is crucial for the outcome of total hip arthroplasty. Recently, 2D pelvic X-ray radiographs have been replaced by 3D CT. However, CT suffers from relatively high radiation dosage and cost. An alternative is to reconstruct a 3D patient-specific volume data from 2D X-ray images.

Methods

In this paper, based on a fully automatic image segmentation algorithm, we propose a new control point-based 2D–3D registration approach for a deformable registration of a 3D volumetric template to a limited number of 2D calibrated X-ray images and show its application to personalized reconstruction of 3D volumes of the proximal femur. The 2D–3D registration is done with a hierarchical two-stage strategy: the scaled-rigid 2D–3D registration stage followed by a regularized deformable B-spline 2D–3D registration stage. In both stages, a set of control points with uniform spacing are placed over the domain of the 3D volumetric template first. The registration is then driven by computing updated positions of these control points with intensity-based 2D–2D image registrations of the input X-ray images with the associated digitally reconstructed radiographs, which allows computing the associated registration transformation at each stage.

Results

Evaluated on datasets of 44 patients, our method achieved an overall surface reconstruction accuracy of \(0.9 \pm 0.2\,\hbox {mm}\) and an average Dice coefficient of \(94.4 \pm 1.1\,\%\). We further investigated the cortical bone region reconstruction accuracy, which is important for planning cementless total hip arthroplasty. An average cortical bone region Dice coefficient of \(85.1 \pm 2.9\,\%\) and an inner cortical bone surface reconstruction accuracy of \(0.7 \pm 0.2\,\hbox {mm}\) were found.

Conclusions

In summary, we developed a new approach for reconstruction of 3D personalized volumes of the proximal femur from 2D X-ray images. Comprehensive experiments demonstrated the efficacy of the present approach.

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Acknowledgments

The QCT data of 39 cadaveric femurs in Group I were provided by Dr. P. Zysset. The paper is partially supported by the Japanese-Swiss Science and Technology Cooperation Program and the Swiss National Science Foundation (SNSF) Project No. 205321_138009/1. M. Tannast received support from SNSF via Project No. PP00P3_144856.

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Authors and Affiliations

  1. Institute for Surgical Technology and Biomechanics, University of Bern, Stauffacherstr. 78, Bern, 3014, Switzerland

    Weimin Yu, Chengwen Chu & Guoyan Zheng

  2. Department of Orthopaedic Surgery, Inselspital, University of Bern, Bern, Switzerland

    Moritz Tannast

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  1. Weimin Yu
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  2. Chengwen Chu
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  4. Guoyan Zheng
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Correspondence to Guoyan Zheng.

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Informed consent was obtained from all individual participants included in the study.

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Yu, W., Chu, C., Tannast, M. et al. Fully automatic reconstruction of personalized 3D volumes of the proximal femur from 2D X-ray images. Int J CARS 11, 1673–1685 (2016). https://doi.org/10.1007/s11548-016-1400-9

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  • DOI: https://doi.org/10.1007/s11548-016-1400-9

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