Balestra, Steven; Schumann, S.; Heverhagen, Johannes; Nolte, Lutz-Peter; Zheng, Guoyan (2014). Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint. In: Stoyanov, Danail; Collins, D. Louis; Sakuma, Ichiro; Abolmaesumi, Purang; Jannin, Pierre (eds.) IPCAI 2014, LNCS 8498. Lecture Notes in Computer Science: Vol. 8498 (pp. 128-137). Cham: Springer 10.1007/978-3-319-07521-1_14
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In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.