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Thesis

Deep learning techniques to bridge the gap between 2D and 3D ultrasound imaging

Abstract:

Three-dimensional (3D) ultrasound imaging has contributed to our understanding of fetal developmental processes in the womb by providing rich contextual information of the inherently 3D anatomies. However, its use is limited in clinical settings, due to the high purchasing costs and limited diagnostic practicality. Freehand two-dimensional (2D) ultrasound imaging, in contrast, is routinely used in standard obstetric exams. The low cost and portability of 2D ultrasound render it uniquely su...

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Division:
MPLS
Department:
Engineering Science
Sub department:
Institute of Biomedical Engineering
Research group:
Oxford Machine Learning in NeuroImaging Lab
Oxford college:
Pembroke College
Role:
Author

Contributors

Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Sub department:
Computer Science
Research group:
Oxford Machine Learning in NeuroImaging Lab
Oxford college:
Pembroke College
Role:
Supervisor
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Engineering Science
Research group:
Visual Geometry Group
Role:
Supervisor
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Institute of Biomedical Engineering
Oxford college:
St Hilda's College
Role:
Supervisor
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Institute of Biomedical Engineering
Oxford college:
Mansfield College
Role:
Examiner
ORCID:
0000-0001-8139-3480
Role:
Examiner
More from this funder
Name:
R C Lee Centenary Scholarship
Funding agency for:
Yeung, PH
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford
DOI:

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