We present a computational method for real-time, patient-specific simulation of 2D ultrasound (US) images. The method uses a large number of tracked ultrasound images to learn a function that maps position and orientation of the transducer to ultrasound images. This is a first step towards realistic patient-specific simulations that will enable improved training and retrospective examination of complex cases. Our models can simulate a 2D image in under 4 ms (well within real-time constraints), and produce simulated images that preserve the content (anatomical structures and artefacts) of real ultrasound images.
CITATION STYLE
Magnetti, C., Zimmer, V., Ghavami, N., Skelton, E., Matthew, J., Lloyd, K., … Gomez, A. (2020). Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time. In Communications in Computer and Information Science (Vol. 1248 CCIS, pp. 423–435). Springer. https://doi.org/10.1007/978-3-030-52791-4_33
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