Birth4Cast – A Digital Twin of Childbirth (LAPEERR_U26SCI)
Key Details
- Application Deadline
- Wednesday 10 December 2025, midnight GMT
- Location
- UEA
- Funding Type
- Competition funded project (Home students only)
- Start Date
- 1 October 2026
- Mode of Study
- Full-time
- Programme Type
- PhD
)
Welcome to Norwich
According to the Sunday Times, this city is one of the best places to live in the UK.
Project Description
Project Supervisor - Professor Rudy Lapeer
The Birth4Cast “Digital Twin” aims to create a subject-specific computational biomechanics simulator of childbirth from prenatal fetal MRI scans of pregnant women. It will build on the already existing BirthView simulator that renders a virtual fetus and the maternal pelvic anatomy on a screen whilst visualising the interactive contact between them that leads to the delivery of the virtual fetus. A subject-specific version of such a simulator would be capable to affect the mode of delivery by predicting the outcome if no intrapartum interventions were to be attempted. For example, if the digital twin simulator were to predict that a natural or “physiological” childbirth would be unlikely to succeed, then the clinical team in consultation with the pregnant person could decide on an elective Caesarean Section (CS) that would be preferred over the emergency CS that would likely result if a natural childbirth would be attempted.
The PhD project will focus on the medical image processing aspect of the Birth4Cast simulator by researching and developing automated image segmentation procedures to extract the pelvic floor muscle complex and the fetal head from the fetal MRI scans. Additionally, mesh modelling techniques will be developed to create 3D Finite Element (FE) mesh models from the segmented fetal and maternal anatomy. These FE models will then be registered with the “baseline” BirthView simulator to create the subject-specific Birth4Cast digital twin. Subject-specific digital twins that have been created throughout the project will run simulations that will be validated against subject-specific data of the real outcome. This will be an iterative process, aimed at finetuning the simulator’s biomechanical parameters, to improve its predictive capabilities to match the real outcome as closely as possible.
Entry Requirements
Acceptable first degree - Computer Science, Engineering, Physics or Mathematics.
The standard minimum entry requirement is 2:1.
The candidate is expected to have completed a final year project with a strong scientific element and having obtained a mark above 70%.
Funding
This PhD project is in a competition for a Faculty of Science funded studentship. Funding is available to UK applicants and comprises ‘home’ tuition fees and an annual stipend for 3 years.