A new AI model could help radiologists identify brain abnormalities - helping radiologists triage and speed up diagnoses.
A new AI model could help radiologists identify brain abnormalities in MRI scans for all conditions including stroke, multiple sclerosis and brain tumours.
The study, led by researchers at King's College London and published in Radiology AI, shows how AI could address the growing backlogs due to radiologist shortages as well as an increasing demand for MRIs year on year for over a decade.
These backlogs could result in treatment delays and poorer patient outcomes because MRI scans are vital for diagnosing and monitoring a range of brain conditions such as tumours, strokes and aneurysms.
AI could help ease the pressure on radiology departments by triaging scans and increasing reporting speeds.
To do this, the model was first asked to distinguish between 'normal' and 'abnormal' scans, which it did accurately when compared to assessments made by expert radiologists.
It was then tested on specific conditions - using new MRI scans which weren't included in the training data - such as a stroke, multiple sclerosis and brain tumours, and was able to recognise these accurately.
Most AI models are currently built with large datasets, manually labelled by expert radiologists - which are expensive and time-consuming to produce.
