Conference item
A dual adversarial calibration framework for automatic fetal brain biometry
- Abstract:
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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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- Files:
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(Accepted manuscript, 9.2MB)
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- Publisher copy:
- 10.1109/ICCVW54120.2021.00363
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Authors
Bibliographic Details
- 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:
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978-1-6654-0191-3
- EISSN:
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2473-9944
- ISSN:
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2473-9936
- ISBN:
- 978-1-6654-0192-0
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1236992
- Local pid:
- pubs:1236992
- Deposit date:
- 2022-05-31
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2021
- Rights statement:
- © IEEE 2021
- Notes:
- This paper was presented at the IEEE/CVF International Conference on Computer Vision Workshops (ICCVW 2021), 11th-17th October 2021, Montreal, BC, Canada.
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