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Generating controllable ultrasound images of the fetal head

Abstract:

Synthesis of anatomically realistic ultrasound images could be potentially valuable in sonographer training and to provide training images for algorithms, but is a challenging technical problem. Generating examples where different image attributes can be controlled may also be useful for tasks such as semi-supervised classification and regression to augment costly human annotation. In this paper, we propose using an information maximizing generative adversarial network with a least-squares lo...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0002-3060-3772
Publisher:
IEEE Publisher's website
Pages:
1761-1764
Publication date:
2020-05-22
Acceptance date:
2020-01-07
Event title:
17th IEEE International Symposium on Biomedical Imaging (ISBI 2020)
Event location:
Iowa City, Iowa, USA
Event website:
http://2020.biomedicalimaging.org/
Event start date:
2020-04-03T00:00:00Z
Event end date:
2020-04-07T00:00:00Z
DOI:
EISBN:
9781538693308
EISSN:
1945-8452
ISSN:
1945-7928
Pubs id:
1112019
Local pid:
pubs:1112019
ISBN:
9781538693315

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