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A dual adversarial calibration framework for automatic fetal brain biometry

Abstract:

This paper presents a novel approach to automatic fetal brain biometry motivated by needs in low- and medium-income countries. Specifically, we leverage high-end (HE) ultrasound images to build a biometry solution for low-cost (LC) point-of-care ultrasound images. We propose a novel unsupervised domain adaptation approach to train deep models to be invariant to significant image distribution shift between the image types. Our proposed method, which employs a Dual Adversarial Calibration (DAC)...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/ICCVW54120.2021.00363

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Publisher:
IEEE Publisher's website
Pages:
3239-3247
Host title:
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops (ICCVW 2021)
Publication date:
2021-11-24
Event title:
IEEE/CVF International Conference on Computer Vision Workshops (ICCVW 2021)
Event location:
Montreal, BC, Canada
Event website:
https://iccv2021.thecvf.com/home
Event start date:
2021-10-11T00:00:00Z
Event end date:
2021-10-17T00:00:00Z
DOI:
EISBN:
978-1-6654-0191-3
EISSN:
2473-9944
ISSN:
2473-9936
ISBN:
978-1-6654-0192-0
Language:
English
Keywords:
Pubs id:
1236992
Local pid:
pubs:1236992
Deposit date:
2022-05-31

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