Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time

Cesare Magnetti; Veronika Zimmer; Nooshin Ghavami; Emily Skelton; Jacqueline Matthew; Karen Lloyd; Jo Hajnal; Julia A. Schnabel; Alberto Gomez

doi:10.1007/978-3-030-52791-4_33

Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time

Cesare Magnetti, Veronika Zimmer, Nooshin Ghavami, Emily Skelton, Jacqueline Matthew, Karen Lloyd, Jo Hajnal, Julia A. Schnabel, Alberto Gomez

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Medical Image Understanding and Analysis - 24th Annual Conference, MIUA 2020, Proceedings
Editors	Bartlomiej W. Papiez, Ana I.L. Namburete, Mohammad Yaqub, J. Alison Noble, Mohammad Yaqub
Publisher	Springer
Pages	423-435
Number of pages	13
ISBN (Print)	9783030527907
DOIs	https://doi.org/10.1007/978-3-030-52791-4_33
State	Published - 2020
Externally published	Yes
Event	24th Annual Conference on Medical Image Understanding and Analysis, MIUA 2020 - Oxford, United Kingdom Duration: 15 Jul 2020 → 17 Jul 2020

Publication series

Name	Communications in Computer and Information Science
Volume	1248 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	24th Annual Conference on Medical Image Understanding and Analysis, MIUA 2020
Country/Territory	United Kingdom
City	Oxford
Period	15/07/20 → 17/07/20

Keywords

Deep learning
Simulation
Ultrasound

Access to Document

10.1007/978-3-030-52791-4_33

Cite this

Magnetti, C., Zimmer, V., Ghavami, N., Skelton, E., Matthew, J., Lloyd, K., Hajnal, J., Schnabel, J. A., & Gomez, A. (2020). Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time. In B. W. Papiez, A. I. L. Namburete, M. Yaqub, J. A. Noble, & M. Yaqub (Eds.), Medical Image Understanding and Analysis - 24th Annual Conference, MIUA 2020, Proceedings (pp. 423-435). (Communications in Computer and Information Science; Vol. 1248 CCIS). Springer. https://doi.org/10.1007/978-3-030-52791-4_33

Magnetti, Cesare ; Zimmer, Veronika ; Ghavami, Nooshin et al. / Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time. Medical Image Understanding and Analysis - 24th Annual Conference, MIUA 2020, Proceedings. editor / Bartlomiej W. Papiez ; Ana I.L. Namburete ; Mohammad Yaqub ; J. Alison Noble ; Mohammad Yaqub. Springer, 2020. pp. 423-435 (Communications in Computer and Information Science).

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title = "Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time",

abstract = "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.",

keywords = "Deep learning, Simulation, Ultrasound",

author = "Cesare Magnetti and Veronika Zimmer and Nooshin Ghavami and Emily Skelton and Jacqueline Matthew and Karen Lloyd and Jo Hajnal and Schnabel, {Julia A.} and Alberto Gomez",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 24th Annual Conference on Medical Image Understanding and Analysis, MIUA 2020 ; Conference date: 15-07-2020 Through 17-07-2020",

year = "2020",

doi = "10.1007/978-3-030-52791-4_33",

language = "English",

isbn = "9783030527907",

series = "Communications in Computer and Information Science",

publisher = "Springer",

pages = "423--435",

editor = "Papiez, {Bartlomiej W.} and Namburete, {Ana I.L.} and Mohammad Yaqub and Noble, {J. Alison} and Mohammad Yaqub",

booktitle = "Medical Image Understanding and Analysis - 24th Annual Conference, MIUA 2020, Proceedings",

}

Magnetti, C, Zimmer, V, Ghavami, N, Skelton, E, Matthew, J, Lloyd, K, Hajnal, J, Schnabel, JA & Gomez, A 2020, Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time. in BW Papiez, AIL Namburete, M Yaqub, JA Noble & M Yaqub (eds), Medical Image Understanding and Analysis - 24th Annual Conference, MIUA 2020, Proceedings. Communications in Computer and Information Science, vol. 1248 CCIS, Springer, pp. 423-435, 24th Annual Conference on Medical Image Understanding and Analysis, MIUA 2020, Oxford, United Kingdom, 15/07/20. https://doi.org/10.1007/978-3-030-52791-4_33

Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time. / Magnetti, Cesare; Zimmer, Veronika; Ghavami, Nooshin et al.
Medical Image Understanding and Analysis - 24th Annual Conference, MIUA 2020, Proceedings. ed. / Bartlomiej W. Papiez; Ana I.L. Namburete; Mohammad Yaqub; J. Alison Noble; Mohammad Yaqub. Springer, 2020. p. 423-435 (Communications in Computer and Information Science; Vol. 1248 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time

AU - Magnetti, Cesare

AU - Zimmer, Veronika

AU - Ghavami, Nooshin

AU - Skelton, Emily

AU - Matthew, Jacqueline

AU - Lloyd, Karen

AU - Hajnal, Jo

AU - Schnabel, Julia A.

AU - Gomez, Alberto

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

KW - Deep learning

KW - Simulation

KW - Ultrasound

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SN - 9783030527907

T3 - Communications in Computer and Information Science

SP - 423

EP - 435

BT - Medical Image Understanding and Analysis - 24th Annual Conference, MIUA 2020, Proceedings

A2 - Papiez, Bartlomiej W.

A2 - Namburete, Ana I.L.

A2 - Yaqub, Mohammad

A2 - Noble, J. Alison

A2 - Yaqub, Mohammad

PB - Springer

T2 - 24th Annual Conference on Medical Image Understanding and Analysis, MIUA 2020

Y2 - 15 July 2020 through 17 July 2020

ER -

Magnetti C, Zimmer V, Ghavami N, Skelton E, Matthew J, Lloyd K et al. Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time. In Papiez BW, Namburete AIL, Yaqub M, Noble JA, Yaqub M, editors, Medical Image Understanding and Analysis - 24th Annual Conference, MIUA 2020, Proceedings. Springer. 2020. p. 423-435. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-52791-4_33

Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time

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Keywords

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