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Weakly supervised learning of placental ultrasound images with residual networks

Abstract:

Accurate classification and localization of anatomical structures in images is a precursor for fully automatic image-based diagnosis of placental abnormalities. For placental ultrasound images, typically acquired in clinical screening and risk assessment clinics, these structures can have quite indistinct boundaries and low contrast, and image-level interpretation is a challenging and time-consuming task even for experienced clinicians. In this paper, we propose an automatic classification mo...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-319-60964-5_9

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Division:
MSD
Department:
Women's and Reproductive Health
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
Publisher:
Springer Publisher's website
Journal:
Annual Conference on Medical Image Understanding and Analysis (MIUA 2017) Journal website
Host title:
Annual Conference on Medical Image Understanding and Analysis (MIUA 2017)
Publication date:
2017-06-22
Acceptance date:
2017-04-19
DOI:
ISSN:
1865-0929
Source identifiers:
709966
ISBN:
9783319609638
Pubs id:
pubs:709966
UUID:
uuid:c59de97a-e157-4b2a-8836-b967855b958f
Local pid:
pubs:709966
Deposit date:
2017-10-03

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