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Title: Ultrasound segmentation tools and their application to assess fetal nutritional health
Author: Rackham, Thomas
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2016
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Maternal diet can have a great impact on the health and development of the fetus. Poor fetal nutrition has been linked to the development of a set of conditions in later life, such as coronary heart disease, type 2 diabetes and hypertension, while restricted growth can result in hypogylcemia, hypocalcemia, hypothermia, polycythemia, hyperbilirubinemia and cerebral palsy. High alcohol consumption during pregnancy can result in Fetal Alcohol Syndrome, a condition that can cause growth retardation, lowered intelligence and craniofacial defects. Current biometric assessment of the fetus involves size-based measures which may not accurately portray the state of fetal development, since they cannot differentiate cases of small-but-healthy or large-but-unhealthy fetuses. This thesis aims to outline a set of more appropriate measures of accurately capturing the state of fetal development. Specifically, soft tissue area and liver volume measurement are examined, followed by facial shape characterisation. A number of tools are presented which aim to allow clinicians to achieve accurate segmentations of these landmark regions. These are modifications on the Live Wire algorithm, an interactive segmentation method in which the user places a number of anchor points and a minimum cost path is calculated between the previous anchor point and the cursor. This focuses on giving the clinician intuitive control over the exact position of the segmented contour. These modifications are FA-S Live Wire, which utilises Feature Asymmetry and a weak shape constraint, ASP Live Wire, which is a 3D expansion of Live Wire, and FA-O Live Wire, which uses Feature Asymmtery and Local Orientation to guide the segmentation process. These have been designed with each of the specific biometric landmarks in mind. Finally, a method of characterising fetal face shape is proposed, using a combination of the segmentation methods described here and a simple shape model with a parameterised b-spline meshing approach to facial surface representation.
Supervisor: Noble, Alison Sponsor: Engineering and Physical Sciences Research Council ; Wellcome Trust ; US National Institute of Alcohol Abuse and Alcoholism ; Research Councils UK
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Image processing ; Image segmentation ; Computer vision in medicine ; Ultrasound in Obstetrics ; Fetus--Ultrasonic imaging ; Fetal alcohol syndrome ; Fetal growth retardation ; Analytic Signal ; Monogenic Signal ; Live Wire ; Feature Asymmetry ; Shape Model