A 2D 3D registration with low dose radiographic system for in vivo kinematic studies

The knowledge of the poses and the positions of the knee bones and prostheses is of a great interest in the orthopedic and biomechanical applications. In this context, we use an ultra low dose bi-planar radiographic system called EOS to acquire two radiographs of the studied bones in each position. In this paper, we develop a new method for 2D 3D registration based on the frequency domain to determine the poses and the positions during quasi static motion analysis for healthy and prosthetic knees. Data of two healthy knees and four knees with unicompartimental prosthesis performing three different poses (full extension, 30° and 60° of flexion) were used in this work. The results we obtained are in concordance with the clinical accuracy and with the accuracy reported in other previous studies.

[1]  M. Marcacci,et al.  A roentgen stereophotogrammetric analysis of unicompartmental knee arthroplasty. , 2002, The Journal of arthroplasty.

[2]  E. Ntasis,et al.  Real time digital reconstructed radiograph (DRR) rendering in frequency domain , 1999, Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. N.

[3]  C. Roux,et al.  Registration of Low Dose bi-Planar Acquisitions for Motion Analysis , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  W. Eric L. Grimson,et al.  2D-3D rigid registration of X-ray fluoroscopy and CT images using mutual information and sparsely sampled histogram estimators , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[5]  G Selvik,et al.  Active knee motion after cruciate ligament rupture. Stereoradiography. , 1988, Acta orthopaedica Scandinavica.

[6]  R. Yang,et al.  Optimal interpolating windowed discrete Fourier transform algorithms for harmonic analysis in power systems , 2003 .

[7]  Gengsheng Lawrence Zeng,et al.  Medical Image Reconstruction: A Conceptual Tutorial , 2010 .

[8]  J. D. De Guise,et al.  3D reconstruction of the proximal femur with low-dose digital stereoradiography , 2004, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[9]  Y. Koga,et al.  Three-dimensional lower extremity alignment assessment system: application to evaluation of component position after total knee arthroplasty. , 2004, The Journal of arthroplasty.

[10]  Mark R. Pickering,et al.  A new multi-modal similarity measure for fast gradient-based 2D-3D image registration , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[11]  B. Beynnon,et al.  Accuracy and repeatability of Roentgen stereophotogrammetric analysis (RSA) for measuring knee laxity in longitudinal studies. , 2001, Journal of biomechanics.

[12]  Kyehyun Kim,et al.  Fast 2D-3D registration using GPU-based preprocessing , 2005, Proceedings of 7th International Workshop on Enterprise networking and Computing in Healthcare Industry, 2005. HEALTHCOM 2005..

[13]  Baba C. Vemuri,et al.  Real-Time DRR Generation Using Cylindrical Harmonics , 2002, MICCAI.

[14]  Jürgen Weese,et al.  A Comparison of Simularity Measures for use in 2D-3D Medical Image Registration , 1998, MICCAI.

[15]  Manish Agarwal,et al.  Computerized Medical Imaging and Graphics Automated Identification of Anatomical Landmarks on 3d Bone Models Reconstructed from Ct Scan Images , 2022 .

[16]  M. Levoy,et al.  Fast volume rendering using a shear-warp factorization of the viewing transformation , 1994, SIGGRAPH.

[17]  Takeo Kanade,et al.  Post-Operative Measurement of Acetabular Cup Position Using X-Ray/CT Registration , 2000, MICCAI.

[18]  Benjamin B. Kimia,et al.  2D-3D registration based on shape matching , 2000, Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis. MMBIA-2000 (Cat. No.PR00737).

[19]  Richard D. Komistek,et al.  A robust method for registration of three-dimensional knee implant models to two-dimensional fluoroscopy images , 2003, IEEE Transactions on Medical Imaging.

[20]  Jürgen Weese,et al.  A comparison of similarity measures for use in 2-D-3-D medical image registration , 1998, IEEE Transactions on Medical Imaging.

[21]  Wolfgang Birkfellner,et al.  Fast DRR Generation for 2D/3D Registration , 2005, MICCAI.

[22]  Meritxell Bach Cuadra,et al.  Bi-planar 2D-to-3D registration in Fourier domain for stereoscopic x-ray motion tracking , 2008, SPIE Medical Imaging.

[23]  P. Abolmaesumi,et al.  2D/3D Registration of Multiple Bones , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.