Computers Make Three Minute Stroke Diagnosis

Computer-assisted stroke diagnosis could provide time-strapped doctors with a reliable second opinion.

AsianScientist (May 22, 2015) – Researchers have developed a computer-aided detection system that can detect if a patient was struck by ischemic stroke or hemorrhagic stroke. With an accuracy of 90 percent—comparable to that of human specialists, the artificial intelligence system is three to five times faster, making a diagnosis in just three minutes.

Providing treatment to acute stroke patients within the golden hours of stroke treatment, i.e. three hours of stroke onset, is vital to saving lives. However, stroke specialists do not work around the clock, increasing the risk of misdiagnosis and delayed diagnosis of acute stroke.

The brain scan analysis system developed by a team at The Hong Kong Polytechnic University (PolyU) could serve as a second opinion for frontline medical doctors, enabling timely and appropriate treatment for stroke patients.

Developed by experts from the Department of Health Technology and Informatics at PolyU, the computer-aided detection for stroke (CAD stroke) technology combines sophisticated calculations, artificial intelligence and pathology to help medical professionals achieve speedy and accurate diagnosis.

The first part of the system is an algorithm for automatic extraction of areas of suspected region of interest. A computed tomography (CT) scan uses X-rays to take pictures of the brain in slices. When blood flow to the brain is blocked, an area of the brain turns softer or decreases in density due to insufficient blood flow, pointing to an ischemic stroke.

The second part is an artificial neural network to classify region of interest for stroke. The CAD stroke computer ‘learns’ the defining features of stroke and performs automated reasoning. CT scans are fed into the CAD stroke computer, which will make sophisticated calculations and comparisons to locate areas suspected of insufficient blood flow. It detects where the images look ‘abnormal’ and will be highlighted for doctors’ review.

Early changes including loss of insular ribbon, loss of sulcus and dense middle cerebral artery (MCA) signs will appear as ‘abnormalities’, helping doctors determine if blood clots are present. As the system is able to detect subtle change in density, it is also able to detect hemorrhagic stroke which is presented as increase in tissue density.

Equipped with the built-in artificial intelligence feature, the CAD stroke technology can learn by experience. With every scan passing through, along with feedback from stroke specialists, the application will improve its accuracy over time.

The life-saving application can also detect subtle and minute changes in the brain that would escape the eye of even an experienced specialist, slashing the chances of missed diagnosis. False-positive and false-negative cases and other less serious conditions that mimic a stroke can also be ruled out, allowing a fully-informed decision to be made.


Source: The Hong Kong Polytechnic University.
Disclaimer: This article does not necessarily reflect the views of AsianScientist or its staff.

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