Abstract
Intraoperative ultrasound is an imaging modality frequently used to provide delineation of tissue boundaries. This paper proposes a simulation platform that enables rehearsal of patient-specific deformable ultrasound scanning in real-time, using preoperative CT as the data source. The simulation platform was implemented within the GPU-accelerated NVIDIA FleX position-based dynamics framework. The high-resolution particle model is used to deform both surface and volume meshes. The latter is used to compute the barycentric coordinates of each simulated ultrasound image pixel in the surrounding volume, which is then mapped back to the original undeformed CT volume. To validate the computation of simulated ultrasound images, a kidney phantom with an embedded tumour was CT-scanned in the rest position and at five different levels of probe-induced deformation. Measures of normalised cross-correlation and similarity between features were adopted to compare pairs of simulated and ground truth images. The accurate results demonstrate the potential of this approach for clinical translation.
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Acknowledgements
The authors are grateful for the support from the Northwick Park Institute for Medical Research, the Hamlyn Centre for Robotic Surgery and from The Imperial NIHR Biomedical Research Centre (BRC).
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Camara, M., Mayer, E., Darzi, A., Pratt, P. (2017). Simulation of Patient-Specific Deformable Ultrasound Imaging in Real Time. In: Cardoso, M., et al. Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound. BIVPCS POCUS 2017 2017. Lecture Notes in Computer Science(), vol 10549. Springer, Cham. https://doi.org/10.1007/978-3-319-67552-7_2
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DOI: https://doi.org/10.1007/978-3-319-67552-7_2
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