Artificial intelligence-driven management of brain tumours

Approximately 25,000 patients are diagnosed with a brain tumour every year in the UK. Meningiomas and pituitary adenomas
are the first and third most common primary tumour, accounting for over 50% of all primary brain tumours. Brain metastases
affect up to 40% of patients with extracranial primary cancer.
Patients with brain tumours require individualized patient management. The automated detection and segmentation of brain
tumours could help personalise and standardise patient management and significantly improve clinical workflow.
We have previously developed a fully-automated AI framework to segment a vestibular schwannoma (a type of brain tumour)
from MRI achieving state-of-the-art results on which this project will build on.

This project aims to develop deep learning models to: 1) detect and automatically segment various non-glial brain tumours
(meningioma, pituitary adenoma, brain metastases) using MRI; and 2) develop compositive clinical and imaging biomarkers to
predict tumour growth and behaviour (pituitary adenoma, meningioma).