Spectral-based 2D/3D X-ray to CT image rigid registration

M. Freiman; O. Pele; A. Hurvitz; M. Werman; L. Joskowicz

doi:10.1117/12.876365

1 March 2011 Spectral-based 2D/3D X-ray to CT image rigid registration

M. Freiman, O. Pele, A. Hurvitz, M. Werman, L. Joskowicz

Proceedings Volume 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling; 79641B (2011) https://doi.org/10.1117/12.876365
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

We present a spectral-based method for the 2D/3D rigid registration of X-ray images to a CT scan. The method uses a Fourier-based representation to decompose the six rigid transformation parameters problem into a twoparameter out-of-plane rotation and a four-parameter in-plane transformation problems. Preoperatively, a set of Digitally Reconstructed Radiographs (DRRs) are generated offline from the CT in the expected in-plane location ranges of the fluoroscopic X-ray imaging devices. Each DRR is transformed into a imaging device in-plane invariant features space. Intraoperatively, a few 2D projections of the patient anatomy are acquired with an X-ray imaging device. Each projection is transformed into its in-plane invariant representation. The out-of-plane parameters are first computed by maximization of the Normalized Cross-Correlation between the invariant representations of the DRRs and the X-ray images. Then, the in-plane parameters are computed with the phase correlation method based on the Fourier-Mellin transform. Experimental results on publicly available data sets show that our method can robustly estimate the out-of-plane parameters with accuracy of 1.5° in less than 1sec for out-of-plane rotations of 10° or more, and perform the entire registration in less than 10secs.

Citation Download Citation

M. Freiman, O. Pele, A. Hurvitz, M. Werman, and L. Joskowicz "Spectral-based 2D/3D X-ray to CT image rigid registration", Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 79641B (1 March 2011); https://doi.org/10.1117/12.876365

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