Article

D reconstruction of a femoral shape using a parametric model and two 2d fluoroscopic images. Comput Vis Image Underst

Graduate School of Information Science and Electrical Engineering, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan
Proceedings - IEEE International Conference on Robotics and Automation 02/2009; 113(2):202-211. DOI: 10.1016/j.cviu.2008.08.012
Source: DBLP

ABSTRACT

In medical diagnostic imaging, the X-ray CT scanner and the MRI system have been widely used to examine 3D shapes and internal structures of living organisms and bones. However, these apparatuses are generally large and very expensive. Since an appointment is also required before examination, these systems are not suitable for urgent fracture diagnosis in emergency treatment. However, X-ray/fluoroscopy has been widely used as traditional medical diagnosis. Therefore, the realization of the reconstruction of precise 3D shapes of living organisms or bones from a few conventional 2D fluoroscopic images might be very useful in practice, in terms of cost, labor, and radiation exposure. The present paper proposes a method by which to estimate a patient-specific 3D shape of a femur from only two fluoroscopic images using a parametric femoral model. First, we develop a parametric femoral model by the statistical analysis of 3D femoral shapes created from CT images of 56 patients. Then, the position and shape parameters of the parametric model are estimated from two 2D fluoroscopic images using a distance map constructed by the Level Set Method. Experiments using synthesized images, fluoroscopic images of a phantom femur, and in vivo images for hip prosthesis patients are successfully carried out, and it is verified that the proposed system has practical applications.

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    • "In the most general case, the camera parameters are unknown, the 3D model itself usually inherits high complexity (high degrees of freedom even for non-articulated objects), while at the same time image features can be ambiguous, occluded and noisy. There are numerous applications involving the above scenario, such as traffic monitoring with 3D model based tracking [18], hand tracking [9], facial analysis [4] and medical imaging [17]. Such an inference process usually involves three steps: the first aims to determine a compact representation of the 3D model, the second to associate such a representation with the 2D image observation, and the last to recover the optimal parameters of the model. "
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    • "Solving the 2D/3D registration problem has been extensively investigated in medical imaging and computer vision. In [6], the authors propose to segment the femur contours in the X-ray images through a level set technique in order to build a distance map before proceeding to registration. Feature-based registration techniques rely on identifying specific landmarks [7] [9] and thus require the user intervention and a suitable user interface which is not practical an in inter-operative context. "
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    • "In addition, the 3D shape estimation of a parameterized object, such as the shape reconstruction of mathematical plaster models with unknown parameters using a laser range finder [20], or the comparison of multiple cross-section images of a 3D model and a 3D parametric model [21], has also been studied. However, these studies assumed the use of a sufficient number of images or a precise 3D shape taken by a laser range finder, and only a few studies have examined 3D non-rigid shape reconstruction from only a few 2D images [22] [23] [24]. Zheng et al. [24] proposed a similar approach with our method for estimating a femoral shape from fluoroscopic images. "
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    ABSTRACT: In medical diagnostic imaging, the X-ray CT scanner and the MRI system have been widely used to examine 3D shapes and internal structures of living organisms and bones. However, these apparatuses are generally large and very expensive. Since an appointment is also required before examination, these systems are not suitable for urgent fracture diagnosis in emergency treatment. However, X-ray/fluoroscopy has been widely used as traditional medical diagnosis. Therefore, the realization of the reconstruction of precise 3D shapes of living organisms or bones from a few conventional 2D fluoroscopic images might be very useful in practice, in terms of cost, labor, and radiation exposure. The present paper proposes a method by which to estimate a patient-specific 3D shape of a femur from only two fluoroscopic images using a parametric femoral model. First, we develop a parametric femoral model by the statistical analysis of 3D femoral shapes created from CT images of 56 patients. Then, the position and shape parameters of the parametric model are estimated from two 2D fluoroscopic images using a distance map constructed by the Level Set Method. Experiments using synthesized images, fluoroscopic images of a phantom femur, and in vivo images for hip prosthesis patients are successfully carried out, and it is verified that the proposed system has practical applications.
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