Artificial Intelligence for Pediatric Brain Tumor Detection and Prediction of Disease Progression

Ongoing
Data
Asset 18.png

CBTN Data Used

About this

Project

We intend to develop a set of tools which will use artificial intelligence (AI) to aid with the clinical management of pediatric brain tumors. These tools will automatically detect brain tumors in MRI scans, and provide predictions as to what subtype of tumor the patient has. We will also use AI to help detect early signs of disease progression.

Ask The

Scientists

Ask the scientists

What are the goals of this project?

The goals of this project are to automatically segment brain tumours on multi-modal MR images, differentiate tumour malignancy / histology based on MR imaging characteristics and to identify early predictors of tumour progression, and ultimately patient outcome.

What is the impact of this project?

Although previous studies have explored AI-based techniques to do this in adults, fewer studies have focused specifically on paediatric brain tumours.

Specimen Data

The Children's Brain Tumor Network contributed to this project by providing access to the Pediatric Brain Tumor Atlas.

Explore the data in these informatics portals

Cavativa-Logo.png