Scientists are using artificial intelligence to build an accurate MRI scan-understanding system that could change the way doctors diagnose breast cancer.
In a two-year experiment, doctors at South Tees Hospitals NHS Foundation Trust will use a cutting-edge technology to analyse thousands of breast scans from MRI machines throughout the UK.
IntelliScan, which will be developed by ÃÛÌÒ´«Ã½, and Teesside University, combines deep machine learning and advanced image-processing smart algorithms.
It will automatically flag up key watch points on each potential case, which will let radiologists handle many more images faster and more accurately, and help save lives by detecting tumours earlier.
“The technique will provide unique information to support doctors during the diagnostic process,” said Brunel's Sergio Malo. “And the machine learning algorithm will use the doctors’ feedback for further training and for continuous improvement of the detection tool across the UK.”
Once fully developed, the plan is to link the system to breast scans from all MRI systems UK-wide, so it can detect abnormalities and categorise them by severity. Its algorithms will also help doctors predict how well treatment will work on individual patients by comparing their consecutive scans.
IntelliScan’s digital image processing and artificial intelligence decision system will be developed at Brunel Innovation Centre, which specialises in developing algorithms for pattern, defect and anomalies detection, through modelling machine learning and image processing. It has developed expertise in similar technologies such as behaviour modelling and advanced inspection of structures.
Missed or late diagnosis is behind 20% of cancer deaths in the UK, which has the some of the worst cancer survival rates in Western Europe.
The IntelliScan project has received a grant of £830,000 from , an executive non-departmental public body, sponsored by the Department for Business, Energy & Industrial Strategy. The work will completely change how the NHS uses MRI scans to diagnose and treat breast cancer. It combines specialist image processing and machine learning with the Internet of Things, through cloud hosting and remote data processing.
Dr Jianxin Gao, Director of Teesside University’s Healthcare Innovation Centre, added: “This is an exciting project and one that could make considerable and positive changes to the healthcare sector – improving the accuracy and speed of breast cancer MRI analysis. Early detection is crucial to survival and this technology could help to save the lives of thousands of patients.”
Hospital radiographers will automatically get highly digitally advanced reports, allowing them to help doctors dramatically improve outcomes for patients.
“The system integrates a series of visualisation, data processing, data communication and decision-support systems which will enable it to dramatically improve access to breast healthcare and cancer treatment compliance,” said Professor Tat-Hean Gan, Brunel Innovation Centre’s director.
Reported by:
Hayley Jarvis,
Media Relations
+44 (0)1895 268176
Hayley.jarvis@brunel.ac.uk