Nigerian Scientist Mary-Brenda Akoda Wins 2026 Prize With AI Technology That Cuts MRI Scans by 90%

Nigerian artificial intelligence researcher Mary-Brenda Akoda has developed a technology capable of reducing Magnetic Resonance Imaging (MRI) scan times by up to 90 per cent, offering a potential solution to delays in medical diagnosis.

Akoda, founder of Genscan AI and a former Microsoft engineer, unveiled details of the innovation, known as GenMRI, during the public presentation of the 2026 Nigeria Prize for Science and Innovation winner organised by Nigeria LNG Limited (NLNG) in Lagos on Tuesday.

The technology uses artificial intelligence to reconstruct diagnostic-quality MRI images from less scanning data, potentially allowing hospitals to examine more patients in less time.

Akoda’s work focuses on challenges facing healthcare facilities, including the limited availability of MRI scanners, the high cost of equipment and the length of conventional scanning procedures.

Personal Tragedy Inspired the Development of GenMRI

Akoda said the idea behind GenMRI emerged after an elderly relative suffered a stroke and needed an urgent MRI scan but encountered lengthy procedures before eventually dying.

The experience prompted her to explore how technology could help reduce delays in diagnosis, particularly in time-sensitive medical emergencies.

“Sadly, his story isn’t unique. Worldwide, someone suffers a stroke every two seconds, and it kills over 6.5 million people annually, while cancer kills over 10 million,” she said.

Her account highlights the potential consequences of delayed access to diagnostic services, especially in healthcare systems where advanced imaging equipment is expensive or insufficient to meet demand.

AI Could Reduce MRI Scans From 20 Minutes to Two

Conventional MRI examinations can take between 15 minutes and 90 minutes, depending on the type of scan and the procedure involved.

Akoda noted that high-quality MRI scanners can cost between $1.5 million and $3.5 million, making the technology financially inaccessible for many healthcare providers.

GenMRI aims to address some of these challenges by using AI to generate diagnostic-quality images from fewer scan data.

According to Akoda, the technology can reduce a 20-minute MRI procedure to approximately two minutes, while a scan that would ordinarily take an hour could be completed in around six minutes.

If the reported time reductions can be reproduced in clinical practice, the technology could help improve scanner availability and reduce waiting times for patients who need medical imaging.

Clinical Assessments Examine the Quality of AI-Generated Images

Akoda said GenMRI had undergone retrospective validation using more than 8,800 MRI images, with findings published in peer-reviewed papers and presented at leading conferences.

She also disclosed that a consultant radiologist at Buckinghamshire NHS Hospital in the United Kingdom conducted a blinded assessment of the technology.

According to Akoda, the assessment found that the GenMRI images were diagnostically equivalent to conventional MRI images in all the cases evaluated.

However, broader clinical validation remains important before the technology can be adopted widely. Its performance must be assessed across different patient groups, scanning procedures and healthcare settings to establish its reliability and suitability for routine use.

Akoda said one of the biggest technical challenges was ensuring that the system generated images grounded in the individual patient’s scan data rather than producing images that merely appeared realistic.

“The most significant challenge was ensuring that we weren’t just building an AI system that could create any MRI image, but that it was anchored in the patient’s data,” she said.

Genscan AI Targets Wider Deployment by 2027

Genscan AI is working with clinical partners in the United Kingdom, the United States, Kenya and Nigeria to advance the technology towards broader clinical validation, regulatory approval and pilot deployments.

Akoda said the company was targeting wider deployment in the second half of 2027, subject to the necessary development and approval processes.

The company is also seeking additional clinical partners and health innovation funders to support testing and adoption in hospitals.

The next phase will be critical in determining how effectively GenMRI performs outside retrospective assessments and whether it can meet the clinical and regulatory requirements needed for wider use.

NLNG Highlights the Importance of Homegrown Scientific Innovation

Dr Sophia Horsfall, NLNG’s general manager for External Relations and Sustainable Development and a senior management executive, reaffirmed the company’s commitment to encouraging local solutions to healthcare challenges and recognising scientific achievement.

In her welcome address, Horsfall emphasised the importance of innovation and accurate diagnosis in improving health outcomes.

The event also featured goodwill messages from participating organisations, which commended the innovation and acknowledged NLNG’s role in supporting scientific excellence.

Akoda’s recognition through the 2026 Nigeria Prize for Science and Innovation places a spotlight on the potential of locally driven research to address healthcare challenges that extend beyond Nigeria.

While further testing and regulatory clearance will be necessary before GenMRI can be deployed more broadly, its proposed reduction in MRI scan times could offer an important opportunity to improve access to diagnostic imaging if its performance is confirmed through wider clinical use.