SIFT algorithm-based 3D pose estimation of femur

Abstract

To address the lack of 3D space information in the digital radiography of a patient femur, a pose estimation method based on 2D–3D rigid registration is proposed in this study. The method uses two digital radiography images to realize the preoperative 3D visualization of a fractured femur. Compared with the pure Digital Radiography or Computed Tomography imaging diagnostic methods, the proposed method has the advantages of low cost, high precision, and minimal harmful radiation. First, stable matching point pairs in the frontal and lateral images of the patient femur and the universal femur are obtained by using the Scale Invariant Feature Transform method. Then, the 3D pose estimation registration parameters of the femur are calculated by using the Iterative Closest Point (ICP) algorithm. Finally, based on the deviation between the six degrees freedom parameter calculated by the proposed method, preset posture parameters are calculated to evaluate registration accuracy. After registration, the rotation error is less than l.5°, and the translation error is less than 1.2 mm, which indicate that the proposed method has high precision and robustness. The proposed method provides 3D image information for effective preoperative orthopedic diagnosis and surgery planning.