Nigerian AI innovation cuts MRI scan time, wins 2026 NPSI Prize
By Ojoma Akor
A Nigerian-developed artificial intelligence (AI) technology that can reduce magnetic resonance imaging (MRI) scan times by up to 90 percent has won the 2026 Nigeria Prize for Science and Innovation (NPSI).
The technology, GenScan AI (GenMRI), developed by Nigerian AI researcher Mary-Brenda Akoda, uses artificial intelligence to reconstruct diagnostic-quality MRI images from significantly fewer data acquisitions, potentially reducing a 20-minute scan to about two minutes and an hour-long scan to approximately six minutes.
The innovation was unveiled at the public presentation of the 2026 NPSI winner, where health, science and technology stakeholders highlighted its potential to reduce diagnostic delays, improve MRI capacity and expand access to medical imaging.
The General Manager, External Relations and Sustainable Development of the Nigerian LNG Limited (NLNG), Dr. Sophia Horsfall, said accurate and timely diagnosis remains critical to effective medical treatment.
She noted that diagnostic imaging provides clinicians with evidence that cannot always be obtained through physical examination, adding that the earlier such evidence becomes available, the better positioned medical teams are to make critical decisions about patients.
She said MRI procedures can be affected by the time required to acquire images and the difficulty some patients have remaining still because of pain, anxiety, age, or illness.
“These clinical realities provide the context of our all gathering here today,” Horsfall said.
She said GenScan AI was selected as the winning innovation after judges found that it could considerably reduce MRI acquisition time, improve image quality, and accommodate patient motion without requiring new MRI hardware.
“This year’s prize focused on innovations in artificial intelligence, ICT, or digital technologies for development,” she said.
Horsfall explained that NLNG established the prize not only to recognize scientific achievement but also to encourage research that addresses Nigeria’s challenges and delivers practical benefits to society.
“The true value of innovation in healthcare is seen in the difference it makes to the people who depend on it,” she said.
‘Every second counts’
Presenting the winning innovation, Akoda said the technology was inspired partly by a personal experience involving a loved one who suffered a stroke and required urgent medical imaging.
She said delays in accessing scans can have serious consequences in emergencies where timely diagnosis can determine treatment options.
“Every second counts,” Akoda said, recalling how her loved one’s condition deteriorated while waiting for an urgent scan.
She noted that stroke, cancer, accidents, and several other conditions require timely diagnostic imaging, yet access to MRI remains constrained by the limited number and high cost of scanners.
According to Akoda, MRI examinations can take between 15 minutes and an hour or longer, depending on the scan type.
Patients who move during the procedure may produce blurred images and require repeat scans, while children, elderly patients and critically ill patients may sometimes require sedation to remain still.
She said the combination of limited MRI capacity, long scan times and the high cost of MRI machines contributes to diagnostic backlogs.
“A high-quality MRI scan costs anywhere from $1.5 million and above, and can get to $3.5 million and above, depending on what you buy,” she said.
She added that MRI equipment also has a limited operational lifespan, creating an additional financial burden for healthcare facilities.
AI could expand MRI capacity without new scanners.
Akoda said GenScan AI addresses the problem by enabling MRI systems to produce diagnostic-quality images using only a fraction of the data traditionally acquired during a scan.
She compared conventional MRI acquisition to assembling a picture puzzle containing thousands of pieces.
“We have taught our AI system to be able to take just a few of those pieces, say 100 or 200 of those, and still be able to put back the full diagnostic quality image,” she explained.
The technology does not require hospitals to purchase new MRI hardware or significantly change their existing workflow. Instead, it is designed to reduce the time patients spend inside the scanner.
Akoda said this could result in fewer repeat scans, lower sedation requirements, and increased patient throughput.
She illustrated the potential capacity gains by reducing a hypothetical 20-minute scan to two minutes.
“If we get a 20-minute scan down to two minutes, that means we save 18 minutes,” she said, adding that across 1,000 scans, this would translate into 18,000 minutes, or 300 hours, of scanner capacity.
According to her team’s health economics assessment, even at a four-fold acceleration, the technology could potentially enable a facility to scan more than 40,000 additional patients annually.
Technology developed from research at Imperial College London
Akoda said the research behind GenScan AI began during her postgraduate studies at Imperial College London.
She said the technology had achieved up to 99.7 percent similarity with conventional MRI scans despite a 90 percent reduction in scan time.
The technology has also undergone peer-reviewed research, she said, with findings published at two leading conferences.
However, Akoda said the most important test was whether radiologists could distinguish the AI-accelerated scans from conventional MRI images.
She said consultant radiologists assessed the images without knowing which were conventional and which had been generated using the accelerated technology.
“In that assessment, the consultant radiologists scored the GenScan AI images as diagnostically equivalent to the conventional scan in all the cases that were assessed,” she said.
Backed by UK and international partners
Akoda said the technology has received support from several institutions, including Innovate UK, UK Research and Innovation, and the NHS Clinical Entrepreneur Program.
She said the team also has clinical partners in the UK, United States, Kenya and Nigeria.
In Nigeria, she said, the Chief Medical Director of Asokoro Diagnostic and Medical Center has supported a proposed clinical pilot of the technology.
The next stage, according to Akoda, is regulatory submission and clinical trials, with the team aiming to obtain regulatory approval, conduct pilot deployments and begin commercial deployment in the second half of 2027.
She called on Nigerian diagnostic imaging centers to participate in clinical studies and early-adopter programs, and urged health and innovation funders to support clinical pilots.
She also appealed to the Federal Ministry of Health to endorse a national pilot of the technology.
“We want Nigeria to be a priority in getting this technology rolled out and not an afterthought,” Akocha said.
She said scaling the technology across Nigeria could support faster diagnosis for patients with stroke, cancer, trauma and other conditions requiring medical imaging.
“Ultimately, our vision is that no one should suffer or die because of a delayed diagnosis,” she said.
NPSI maintains a global standard Advisory Board
The Chairman of the NPSI Advisory Board, Prof. Barth Nnaji, said the prize was designed to recognize innovations that solve important problems and have meaningful impact in Nigeria and beyond.
He said the award was not simply a reward for academic research but for an innovation that has demonstrated relevance to real-world problems.
“The prize is not awarded for research. It is given to you because you have done something so important out there in the world that is solving a world problem but has impact in Nigeria,” Nnaji said.
He disclosed that the 2025 competition did not produce a winner because none of the submissions met the Advisory Board’s rigorous standards.
The AI, ICT and digital technology theme was therefore retained, eventually producing GenScan AI as the 2026 winner.
Nnaji said the competition is global and is open to researchers regardless of nationality, noting that previous winners have included international researchers.
He said Akoda’s selection, as a Nigerian woman, demonstrated the global significance of the achievement.
Nnaji also pointed to the importance of medical innovation to Nigeria, particularly given the country’s limited MRI infrastructure and the long waiting times patients can face before accessing diagnostic imaging.
He described the winning technology as an innovation with potential relevance “for the world, not just for Nigeria.”
Government pledges support for commercialization.
The Minister of Innovation, Science and Technology, Dr. Kingsley Tochukwu Udeh, said the Federal Government was focused on strengthening the pathway from research and innovation to commercialization.
He highlighted the role of the National Office for Technology Acquisition and Promotion (NOTAP) in supporting the commercialization and protection of Nigerian innovations.
Represented by the Director-General of the National Board for Technology Incubation, Dr Kazeem Kolawole, the minister said government-backed programs were increasingly connecting Nigerian innovators with international investors and markets.
He cited the government’s Next Gen Innovation Challenge, which received more than 5,000 entries this year, with 298 innovators eventually selected for the program.
The minister also said Innovate UK had selected 20 Nigerian innovators for potential end-to-end investment support.
He offered Akoda an opportunity to participate in the government’s international investor engagement program, particularly because of the interest in health technology innovations.
Minister of Education, Dr Tunji Alausa, enjoined Akoda to protect the intellectual property associated with the innovation, adding that the Federal Ministry of Education would facilitate access to teaching hospitals and Federal Medical Centers for her planned Nigerian pilots.
He described GenScan AI as an example of scientific research being translated into solutions to real human problems.
He said the Ministry of Health should be involved to support the technology’s clinical deployment.
