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

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1248)

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

Ultrasound Simulation Deep learning 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.School of Biomedical Engineering and Imaging SciencesKing’s College LondonLondonUK
  2. 2.Epsom and St Helier University NHS TrustEpsomUK

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