Fast, intuitive, vision-based: Performance metrics for visual registration, instrument guidance, and image fusion

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Abstract

We characterize the performance of an ultrasound+ computed tomography image fusion and instrument guidance system on phantoms, animals, and patients. The system is based on a visual tracking approach. Using multi-modality markers, registration is unobtrusive, and standard instruments do not require any calibration. A novel deformation estimation algorithm shows externally-induced tissue displacements in real time.

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Basafa, E., Hoßbach, M., & Stolka, P. J. (2016). Fast, intuitive, vision-based: Performance metrics for visual registration, instrument guidance, and image fusion. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9958 LNCS, pp. 9–17). Springer Verlag. https://doi.org/10.1007/978-3-319-46472-5_2

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