Join AI Lab Skunkworks to learn how they have been experimenting with using AI to identify tissue growth from CT scans with George Eliot Hospital.
CT scans are used in the detection and understanding of disease. Radiologists currently manually compare two CT scans, taken at different dates, to see whether a patient’s disease has improved, deteriorated or remained unchanged.
This 12-week project investigated the AI techniques that could be applied to the problem and sought to provide a proof of concept (a feasibility study) about whether it was possible to identify organs and growths, report on any changes and highlight areas of concern to the radiologist.
The AI Lab Skunkworks works on demonstrating the potential of AI through proof-of-concepts and upskilling the workforce through a knowledge-sharing model. We help healthcare organisations apply AI to their problems through rapid, agile, iterative projects. By running an open call, we help develop proof of concepts through a 12 week process usually helped by a supplier. We’re excited to present the results of our last project.
Join us for this webinar to learn more:
- About whether AI could be used to identify features in a CT scan and automatically align images to provide radiologists with a quick, trustworthy support tool that would improve early detection and diagnosis of growths and improve patient outcomes.
- Learn more about the current problem radiologists face,
- The AI technique the Roke team used.
- Challenges faced and lessons learned through this project.