Research Topic: Deep learning based Lung Nodule Detection and Cancer risk stratification through the effective Integration of Imaging and Electronic Medical Records (EMRs)
Supervisors: Dr Nishant Ravikumar, Professor Geoff Hall, Professor Alex Frangi
About Rachael: Rachael graduated with a BSc Hons in Biomedical Science and an MSc in Bioinformatics from Newcastle University.
Project description: Lung cancer is the leading cause of cancer related deaths in the UK with very low five- and ten-year survival rates. This is attributed to the fact that the cancer is typically diagnosed at an advanced stage as early detection is particularly challenging. Consequently, there is a clear need for automated and robust systems that facilitate its early detection, diagnosis and treatment. The goal of this project is to develop a system to improve patient management in the context of both lung cancer screening and incidental nodule discovery. The project objectives are defined to this end:
- Develop a fully supervised lung nodule detection framework for automatic assessment of low dose chest CTs.
- Develop a cancer risk stratification system based on the official clinical guidelines.
- Investigate the use of NLP tools for extracting useful information from electronic medical records (EMRs), for subsequent integration with the image analytics.
- Develop a weakly supervised nodule detection algorithm for the effective integration of NLP-derived data from radiology reports with imaging data (low-dose chest CTs).