An synthetic intelligence-powered innovation able to lowering Magnetic Resonance Imaging (MRI) acquisition time by as much as 90 per cent has received the 2026 Nigeria Prize for Science and Innovation (NPSI).
The innovation, GenScan AI, also referred to as GenMRI/C-MORE, was developed by Mary-Brenda Akoda, a Nigerian synthetic intelligence researcher and software program engineer.
Akoda’s emergence because the 2026 NPSI winner is historic, as she turns into the primary lady and first millennial to win the prize as a person recipient.
She emerged winner from a document 237 entries submitted for the 2026 competitors; the best variety of entries obtained for the reason that inception of the prize.
The winner was introduced yesterday in Lagos on the 2026 Press Conference for the Nigeria Prize for Science and Innovation following an impartial analysis by the Prize’s Panel of Judges and subsequent endorsement by the NPSI Advisory Board.
GenScan AI is an AI-powered MRI reconstruction expertise designed to considerably scale back the time required to amass MRI scans whereas sustaining or bettering picture high quality.
Its C-MORE algorithm employs a one-step consistency-model framework to reconstruct MRI photos.
According to the organisers, the expertise has the potential to cut back scan occasions by as much as 90 per cent with out requiring new MRI {hardware}.
The judges stated the innovation stood out among the many three shortlisted entries due to its mixture of scientific innovation, technical soundness, developmental influence and business scalability.
They additionally famous that the expertise might enhance the utilisation of MRI scanners, scale back affected person ready occasions and probably increase entry to medical imaging, notably in resource-constrained healthcare programs resembling Nigeria’s.
The growth is important for a rustic the place entry to superior medical imaging stays constrained by the fee and availability of kit and the time required for examinations.
Rather than requiring hospitals to switch current MRI machines, the innovation is designed to work with current {hardware}, probably providing healthcare suppliers a manner to enhance the effectivity of their imaging companies.
Speaking on the occasion, General Manager, External Relations and Sustainable Development of the Nigeria LNG Limited (NLNG), Dr Sophia Horsfall, stated the emergence of a winner in 2026, after the prize recorded a “no winner” verdict in 2025, demonstrated that the organisers had maintained the integrity and excessive requirements of the competitors.
She stated the 2026 competitors, which retained the theme, “Innovations in Artificial Intelligence, ICT and Digital Technologies for Development,” attracted 237 entries, representing the best quantity recorded for the reason that prize started.
Horsfall stated the return of a winner shouldn’t be interpreted as a leisure of the requirements utilized to the competitors.
“If an entry is declared worthy of the Prize today, we can be confident that it has earned that distinction through a thorough and credible evaluation process,” she stated.
She counseled the Advisory Board and the Panel of Judges for what she described as their professionalism, independence and integrity all through the adjudication course of.
Chairman of the NPSI Advisory Board, Prof. Barth Nnaji, stated the unanimous resolution to recognise GenScan AI mirrored the standard of the innovation and its potential to deal with essential healthcare challenges.
Nnaji stated the adjudication course of was intentionally structured to establish improvements that went past scientific novelty to reveal sensible relevance, measurable influence and prospects for real-world software.
According to him, GenScan AI distinguished itself by combining superior synthetic intelligence with a sensible healthcare software able to bettering the effectivity and accessibility of medical imaging.
2026 award marks the twelfth event on which a profitable work has been recognised within the 22-year historical past of the prize, now rebranded because the Nigeria Prize for Science and Innovation.
Akoda will obtain the US$100,000 prize on the Grand Award Night scheduled to carry on October 9, 2026.
Her tutorial {and professional} background additional underscores the importance of the achievement.
She is a First-Class graduate of Computer Science from Goldsmiths, University of London, and holds a Master of Research with Distinction in Artificial Intelligence and Machine Learning from Imperial College London, the place she was a Google DeepMind Scholar.
Akoda has additionally labored as a software program engineer and AI analysis scientist at Microsoft, together with on the Microsoft Mixed Reality and AI Research Lab in Cambridge.
The NPSI stated GenScan AI’s recognition mirrored the judges’ evaluation that the innovation might translate superior analysis right into a sensible resolution with measurable advantages for healthcare supply.
The expertise’s potential to shorten MRI procedures might allow medical services to conduct extra scans throughout the similar interval, scale back ready occasions for sufferers and enhance the utilisation of current MRI infrastructure.
For Nigeria’s healthcare system, the potential influence could possibly be notably important in settings the place restricted entry to MRI companies is compounded by excessive gear prices and lengthy affected person queues.
NLNG congratulated Akoda and all members within the 2026 competitors, noting that each submission contributes to strengthening Nigeria’s scientific and innovation ecosystem.
The firm additionally counseled the Nigerian media for its continued partnership in selling scientific excellence and inspiring better public curiosity in improvements aimed toward addressing nationwide challenges.
The Nigeria Prize for Science and Innovation stays considered one of NLNG’s flagship initiatives for selling excellence in scientific analysis and technological innovation, with the said goal of encouraging options able to delivering significant and sustainable influence on society.
Wale Igbintade
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