Abstract
This paper introduces a solution that can robustly derive 3D models of musculoskeletal structures from 2D X-ray Images. The present method, as an integrated solution, consists of three components: (1) a musculoskeletal structure immobilization apparatus; (2) an X-ray image calibration phantom; and (3) a statistical shape model-based 2D-3D reconstruction algorithm. These three components are integrated in a systematic way in the present method to derive 3D models of any musculoskeletal structure from 2D X-ray Images in a functional position (e.g., weight-bearing position for lower limb). More specifically, the musculoskeletal structure immobilization apparatus will be used to rigidly fix the X-ray calibration phantom with respect to the underlying anatomy during the image acquisition. The calibration phantom then serves two purposes. For one side, the phantom will allow one to calibrate the projection parameters of any acquired X-ray image. For the other side, the phantom also allows one to track positions of multiple X-ray images of the underlying anatomy without using any additional positional tracker, which is a prerequisite condition for the third component to compute patient-specific 3D models from 2D X-ray images and the associated statistical shape models. Validation studies conducted on both simulated X-ray images and on patients’ X-ray data demonstrate the efficacy of the present solution.
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Zheng, G., Schumann, S., Alcoltekin, A., Jaramaz, B., Nolte, LP. (2016). Patient-Specific 3D Reconstruction of a Complete Lower Extremity from 2D X-rays. In: Zheng, G., Liao, H., Jannin, P., Cattin, P., Lee, SL. (eds) Medical Imaging and Augmented Reality. MIAR 2016. Lecture Notes in Computer Science(), vol 9805. Springer, Cham. https://doi.org/10.1007/978-3-319-43775-0_37
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DOI: https://doi.org/10.1007/978-3-319-43775-0_37
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