Vestibular Schwannoma (VS) is a non-cancerous brain tumour that grows from the inner ear, towards the brain. At current rates, approximately 1 in 1000 people will be diagnosed with a VS in their lifetime. Patients with VS require individualized patient management that may include imaging surveillance, radiation treatment or surgery.
This project aims to: 1) optimise deep learning models to automatically detect and segment VS using MRI; 2) integrate the framework into a tool capable of being deployed in the clinic; and 3) conduct a prospective clinical pilot study to evaluate the clinical impact of using AI-based tool in patient management.
Modern learning-based image-registration methods will be utilised to provide robustness and computational efficiency. The clinical pilot study will provide the foundation for a future multicentre interventional study aimed at assessing clinical effectiveness and health economic impact.
