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Facial anatomical landmark detection using regularized transfer learning with application to fetal alcohol syndrome recognition

Abstract:

Fetal alcohol syndrome (FAS) caused by prenatal alcohol exposure can result in a series of cranio-facial anomalies, and behavioral and neurocognitive problems. Current diagnosis of FAS is typically done by identifying a set of facial characteristics, which are often obtained by manual examination. Anatomical landmark detection, which provides rich geometric information, is important to detect the presence of FAS associated facial anomalies. This imaging application is characterized by large v...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/JBHI.2021.3110680

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Institution:
University of Oxford
Department:
ENGINEERING SCIENCE
Sub department:
Engineering Science
Oxford college:
St Hilda's College
Role:
Author
ORCID:
0000-0002-3060-3772
Publisher:
IEEE Publisher's website
Journal:
IEEE Journal of Biomedical and Health Informatics Journal website
Volume:
26
Issue:
4
Pages:
1591 - 1601
Publication date:
2021-09-08
Acceptance date:
2021-09-01
DOI:
EISSN:
2168-2208
ISSN:
2168-2194
Language:
English
Keywords:
Pubs id:
1193918
Local pid:
pubs:1193918
Deposit date:
2021-09-06

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