Queen’s University Belfast Featured PhD Programmes
Newcastle University Featured PhD Programmes
University of Liverpool Featured PhD Programmes
University of Huddersfield Featured PhD Programmes
University College London Featured PhD Programmes

Deep learning for early detection of cancer recurrence in patients with glioblastoma through imaging

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

About This PhD Project

Project Description

rain tumours are cancer of unmet need and are the most common cause of cancer death in under the 40s. Glioblastoma is the most common primary adult brain tumour and carries one of the worst prognoses amongst human cancers, with a median survival time of about 15 months.

The fundamental question to be answered in this project is: can deep learning be used for early detection and prediction of glioblastoma recurrence through imaging? To this end, we will extend the state-of-the-art using Bayesian recurrent variational auto-encoders (VAE) that will be conditioned on the patient meta-data.

An LSTM-RNN will be trained to approximate the predictive distribution of the next set of MR images, given current images and patient meta-data. We will devise an end-to-end training mechanism that will jointly learn the encoding-decoding maps along with the predictions of the spatiotemporal maps.

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.