PhD position in deep learning with simulated data in medical imaging
Friday 12th June 2020
Closing date: 1 August 2020
Description: The Center for Computational Imaging & Simulation Technologies in Biomedicine at the University of Leeds has a fully-funded 3-year PhD project on offer.
The project develops methods for deep learning with simulated data (DLSD) in medical imaging. By setting up a validated simulation pipeline that models the virtual anatomy, physiology and image formation processes, you will generate synthetic medical images with annotations and use these synthetic images to assist in the training of deep learning models. The aims of the project are flexible but should involve the development of a general framework for DLSD applied to medical imaging, including the incorporation of DLSD in the generative adversarial and weakly supervised learning frameworks. Part of the project should involve the development of a prototype application of DLSD in using real medical imaging data and computer simulations to validate the conceptual developments and demonstrate how DLSD can improve deep learning and solve problems without the necessity of obtaining large quantities of annotated training data.
This PhD project will be undertaken as part of the Centre for Computational Imaging and Simulation Technologies in Biomedicine. We are a 30+ strong research group with research interests in medical imaging, image computing, artificial intelligence, deep learning, and biophysical modelling.
For further details and instructions how to submit your application: https://phd.leeds.ac.uk/project/787-deep-learning-with-simulated-data-in-medical-imaging
For more information, please contact Dr. Toni Lassila at email@example.com.
|Organization||University of Leeds|
|Location||Leeds, United Kingdom|
|Title||PhD position in deep learning with simulated data in medical imaging|