Research Studentship in Ultrasound Neuroimage Analysis

3.5-year D.Phil. studentship

Project title: Longitudinal Tracking of Fetal Brain Development from 3D Ultrasound Images

Supervisor: Dr Ana Namburete

The studentship is part of a project supported by the Royal Academy of Engineering and the EPSRC to undertake research to develop machine learning algorithms to analyse 3D ultrasound images of the developing fetal brain.

 Ultrasound (US) imaging is amongst the first steps in a continuum of pregnancy care. As an affordable brain imaging tool, the resolution of US data allows for qualitative assessment of brain maturation and detection cerebral abnormalities from as early as 18 weeks. The fact that the fetal brain follows a precise spatial and temporal pattern of development, with folds emerging on the brain surface at fixed time points during pregnancy, also suggests the possibility to longitudinally track brain maturation.

The aim of the project is to analyse and quantify volumetric development of fetal brain structures using machine learning techniques and data derived from 3D ultrasound images. The focus of this doctoral project will be the design, development, and testing of an image processing platform to programmatically align (or register) the images, extract structural biomarkers, and quantify changes at different time points. Once these algorithms have been developed, the data will be used to characterize spatial and temporal changes, and explore how individual brain structures evolve during the second and third trimesters of pregnancy. As a close partner of the Nuffield Department of Obstetrics and Gynaecology, our lab has access to the largest database of 3D fetal brain US images. The student will capitalise on this dataset to extract information about neurodevelopment from clinical image data.

 S/he will be a member of the Biomedical Image Analysis Laboratory at the Institute of Biomedical Engineering and will be supervised by Dr Ana Namburete.

Further information on the group can be found here.

Eligibility

This studentship is funded through the UK Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership and is open to both UK students (full award – fees plus stipend) and EU students (partial award – fees only). Full details of the EPSRC eligibility requirements can be found here.

Award Value

University tuition fees are covered at the level set for UK/EU students, as are Oxford college fees (c. £7,432 in total p.a.). The stipend (tax-free maintenance grant) is c. £14,553 p.a. for the first year, and at least this amount for a further two and a half years.

Candidate Requirements

Prospective candidates will be judged according to how well they meet the following criteria:

  • A first class honours degree in Engineering, Physics, Mathematics, Computer Science, or a related discipline;
  • Excellent analytical, interpersonal, as well as written and oral communication skills in English;
  • Strong programming skills (e.g. Python, C/C++, and/or Matlab) and applied mathematical skills.

The following skills are desirable but not essential:

  • Experience in computer vision or machine learning demonstrated by a publication at an international conference or an international journal;
  • Interest in interdisciplinary research.

Application Procedure

Informal enquiries are encouraged and should be addressed to Dr Ana Namburete (ana.namburete@eng.ox.ac.uk).

Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria.  Details are available on the course page of the University website.

Please quote 18ENGIN_02DTP in all correspondence and in your graduate application.

Application deadline:  noon on Friday 19 January 2018 

Start date: October 2018