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NLNG’s Prize-Winning GenScan AI Promises to Cut MRI Times by Up to 90%
Anyone who has waited weeks for an MRI appointment, then lain still inside a loud tube for the better part of an hour, will see why a tool that shortens the scan is worth attention. A Nigerian-built one is now getting its public debut, and it came from an unusual sponsor: a liquefied natural gas company.
Nigeria LNG Limited presented GenScan AI to health-sector stakeholders in Abuja on Monday, October 5. The software is the winning entry of the 2026 Nigeria Prize for Science and Innovation, an award NLNG sponsors, and it was developed by Mary-Brenda Akoda. According to the prize’s advisory board, it uses an artificial intelligence method called the C-MORE algorithm to rebuild MRI images in a single step, with the potential to cut scan acquisition time by as much as 90 percent while keeping image quality the same or better. The most striking claim is that it needs no new MRI hardware, meaning hospitals could in principle run it on scanners they already own.
Why does that matter? An MRI machine builds a picture by collecting a large amount of signal data over time, and the length of a scan largely depends on how much data must be gathered before the computer can reconstruct a clear image. Faster reconstruction methods let a scanner collect less data and still produce a usable picture, which shortens the time the patient spends inside the machine. A shorter exam means a scanner can see more people in a day, waiting lists shrink, and fewer patients, especially children, anxious adults or people in pain, have to stay motionless for long stretches. In a country where advanced diagnostics are scarce in many areas, and where the cost of buying and maintaining MRI equipment limits access, getting more use out of machines already installed is an attractive idea. MRI is widely used to examine the brain, spine, joints and internal organs.
NLNG executives said their interest goes beyond handing out a prize. General Manager for External Relations and Sustainable Development Sophia Horsfall said the company wants research to deliver practical benefits and described GenScan AI as offering the prospect of faster medical imaging and better use of existing equipment. NLNG’s communications manager, Anne-Marie Palmer-Ikuku, said the Abuja session was meant to bring stakeholders together to consider how the technology could be applied in Nigeria’s health sector and what is needed to move it from research into clinical use. The prize carries $100,000, according to reporting on the award.
It is worth being clear about what has and has not been shown. The 90 percent figure is described as a potential reduction, stated as “up to,” and it comes from the prize’s advisory board and NLNG’s statements rather than from published clinical trials or hospital deployment data. None of the reports reviewed say which MRI makes and models the software works with, whether it has been tested on patients, or whether it has regulatory clearance. New reconstruction tools generally have to be checked carefully, since a faster method must still show doctors the same findings, including small abnormalities. That kind of validation, with independent radiologists comparing results against standard scans, is the step between a promising prize winner and a tool used on patients.
The Abuja meeting points to the next stage. Participants were asked what has to happen to move the work toward practical use, which in practice means clinical testing, partnerships with hospitals and imaging centres, and approval from health regulators. For hospital managers, the questions to ask are straightforward: which scanners are supported, how the software is installed and priced, how patient data is handled, and what evidence exists that diagnoses are unchanged.
For readers, the takeaway is cautious optimism. Nigeria has a locally developed medical AI idea with a serious sponsor and a clear practical aim, and the claim that existing machines could do more is exactly the kind that could help health systems with limited budgets. Whether the 90 percent figure holds in real hospitals will decide how much that promise is worth.
