2D/3D registration with the CMA-ES method

Ren Hui Gong; Purang Abolmaesumi

doi:10.1117/12.770331

17 March 2008 2D/3D registration with the CMA-ES method

Ren Hui Gong, Purang Abolmaesumi

Proceedings Volume 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling; 69181M (2008) https://doi.org/10.1117/12.770331
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

In this paper, we propose a new method for 2D/3D registration and report its experimental results. The method employs the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm to search for an optimal transformation that aligns the 2D and 3D data. The similarity calculation is based on Digitally Reconstructed Radiographs (DRRs), which are dynamically generated from the 3D data using a hardware-accelerated technique - Adaptive Slice Geometry Texture Mapping (ASGTM). Three bone phantoms of different sizes and shapes were used to test our method: a long femur, a large pelvis, and a small scaphoid. A collection of experiments were performed to register CT to fluoroscope and DRRs of these phantoms using the proposed method and two prior work, i.e. our previously proposed Unscented Kalman Filter (UKF) based method and a commonly used simplex-based method. The experimental results showed that: 1) with slightly more computation overhead, the proposed method was significantly more robust to local minima than the simplex-based method; 2) while as robust as the UKF-based method in terms of capture range, the new method was not sensitive to the initial values of its exposed control parameters, and has also no special requirement about the cost function; 3) the proposed method was fast and consistently achieved the best accuracies in all compared methods.

Citation Download Citation

Ren Hui Gong and Purang Abolmaesumi "2D/3D registration with the CMA-ES method", Proc. SPIE 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, 69181M (17 March 2008); https://doi.org/10.1117/12.770331

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