Magnetti C, Zimmer V, Ghavami N, Skelton E, Matthew J, Lloyd K, Hajnal J, Schnabel JA, Gomez A (2020)
Publication Type: Conference contribution
Publication year: 2020
Publisher: Springer
Book Volume: 1248 CCIS
Pages Range: 423-435
Conference Proceedings Title: Communications in Computer and Information Science
Event location: Oxford, GBR
ISBN: 9783030527907
DOI: 10.1007/978-3-030-52791-4_33
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.
APA:
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 Bartlomiej W. Papiez, Ana I.L. Namburete, Mohammad Yaqub, J. Alison Noble, Mohammad Yaqub (Eds.), Communications in Computer and Information Science (pp. 423-435). Oxford, GBR: Springer.
MLA:
Magnetti, Cesare, et al. "Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time." Proceedings of the 24th Annual Conference on Medical Image Understanding and Analysis, MIUA 2020, Oxford, GBR Ed. Bartlomiej W. Papiez, Ana I.L. Namburete, Mohammad Yaqub, J. Alison Noble, Mohammad Yaqub, Springer, 2020. 423-435.
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