University of Leeds Featured PhD Programmes
University of Liverpool Featured PhD Programmes
Newcastle University Featured PhD Programmes
University of Huddersfield Featured PhD Programmes
Birkbeck, University of London Featured PhD Programmes

Deep learning for outcome prediction after pelvic radiotherapy

  • Full or part time
  • Application Deadline
    Thursday, August 01, 2019
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Modern radiotherapy is highly optimized with respect to individual patient anatomy, utilising 3D anatomical imaging for treatment planning and guidance. This optimization is, however, fundamentally based on underlying assumptions about the relationships between the radiation dose delivered to specific anatomical structures (tumours and normal tissue) and tumour control and/or treatment toxicity – relationships which are still not well understood. Outcome modelling – relating radiation dose to early and long-term patient outcomes – is consequently an extremely active field of research.

In this project, we use machine learning to predict toxicity and tumour control after pelvic radiotherapy in Cross-sectional data from a population of patients. We will construct a probabilistic statistical atlas describing the spatial patterns of radiosensitivity across the whole population. We will also create patient-specific sensitivity maps to feed into treatment plan optimisation. To alleviate the problem of missing outcome classification data, we will machine learning, e.g. semi-supervised models and cycle GANs.

Funding Notes

Funding will be awarded on a competitive basis.

Email Now

Insert previous message below for editing? 
You haven’t included a message. Providing a specific message means universities will take your enquiry more seriously and helps them provide the information you need.
Why not add a message here
* required field
Send a copy to me for my own records.

Your enquiry has been emailed successfully





FindAPhD. Copyright 2005-2019
All rights reserved.