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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
6-DOF pose estimation from single Ultrasound image using 3D IP models
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Bo Zheng, The University of Tokyo, Ikeuchi Lab, IIS-UT, 4-6-1 Komaba, Meguro-ku, 153-8505, JAPAN
Ryo Ishikawa, Medical Imaging Project, Canon Inc., 3-30-2 Shimomaruko, Ohda-ku, Tokyo, 146-8501, JAPAN
Takeshi Oishi, The University of Tokyo, Ikeuchi Lab, IIS-UT, 4-6-1 Komaba, Meguro-ku, 153-8505, JAPAN
Jun Takamatsu, The University of Tokyo, Ikeuchi Lab, IIS-UT, 4-6-1 Komaba, Meguro-ku, 153-8505, JAPAN
Katsushi Ikeuchi, The University of Tokyo, Ikeuchi Lab, IIS-UT, 4-6-1 Komaba, Meguro-ku, 153-8505, JAPAN
Real-time pose estimation of a free-hand Ultrasound (US) image without any position sensor is desirable for diagnostics and image guidance, but it suffers from poor image quality as a result of processing. The paper confronts this problem by proposing a new 6-DOF pose estimation method based on a fast registration process making use of 3D implicit polynomials (IP). The proposed registration method has some main advantages over the traditional methods. First, our formulation is based on minimization of energy functional derived from IP gradient flow, and thus it is more efficient than traditional registration because it eliminates the cost for calculating point-wise correspondences. Second, the efficient calculation benefits from the property of IP having few coefficients, which means that both the gradient field and its transformation can be calculated in an extremely light manner. Third, applying a real time US image pose estimation, we demonstrate the capabilities of overcoming the limitations of unconstrained free hand US data, resulting in robust and fast pose estimation.
Citation:
Bo Zheng, Ryo Ishikawa, Takeshi Oishi, Jun Takamatsu, Katsushi Ikeuchi, "6-DOF pose estimation from single Ultrasound image using 3D IP models," cvprw, pp.1-8, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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