Self-calibrating ultrasound-to-CT bone registration

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Abstract

We describe a new self-calibrating approach to rigid registration of 3D ultrasound images in which in vivo data acquired for registration are used to simultaneously perform a patient-specific update of the calibration parameters of the 3D ultrasound system. Using a self-calibrating implementation of a point-based registration algorithm, and points obtained from ultrasound images of the femurs and pelves of human cadavers, we show that the accuracy of registration to a CT scan is significantly improved compared with a standard algorithm. This new approach provides an effective means of compensating for errors introduced by the propagation of ultrasound through soft tissue, which currently limit the accuracy of conventional methods where the calibration parameters are fixed to values determined preoperatively using a phantom. © Springer-Verlag Berlin Heidelberg 2005.

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Barratt, D. C., Penney, G., Chan, C. S. K., Slomczykowski, M., Carter, T. J., Edwards, P. J., & Hawkes, D. J. (2005). Self-calibrating ultrasound-to-CT bone registration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3749 LNCS, pp. 605–612). https://doi.org/10.1007/11566465_75

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