Nigerian Ai Scientist to Roll Out Software That Cuts MRI Time By 90 Percent
Nigerian AI scientist Mary-Brenda Akoda plans to launch GenMRI, an AI medical imaging software, in Nigeria and the UK by mid-2027, promising to reduce MRI scan times by up to 90 percent.
Intelligence analysis by Gemini 2.5 Flash
Mary-Brenda Akoda, founder of GenScan AI, has developed GenMRI, an AI-powered solution designed to significantly accelerate MRI scans on existing hospital equipment. This innovation aims to tackle long patient waiting lists and improve diagnostic speed for critical conditions, inspired by Akoda's personal experience with healthcare delays.
Imagine going to the doctor for a special picture of your body, like an X-ray but much more detailed, called an MRI. Usually, you have to lie very still for a long time, sometimes even an hour, in a noisy machine. But a smart scientist from Nigeria, Mary-Brenda Akoda, has invented a special computer program called GenMRI that can make these pictures up to ten times faster! So, a picture that used to take an hour might now only take six minutes. This means doctors can help more people quickly, and kids or older people won't have to stay still for so long.
Analysis
GenMRI Technology
GenMRI is presented as a groundbreaking AI imaging software capable of dramatically accelerating Magnetic Resonance Imaging (MRI) scans. The technology is designed to integrate with existing scanners, eliminating the need for hospitals to invest in new, expensive machinery. It boasts the ability to reduce a typical 20-minute scan to just two minutes, and an hour-long scan to six minutes, representing up to a 90 percent reduction in scan time. This efficiency gain is crucial for increasing patient throughput and alleviating backlogs in medical imaging centers.
The software's efficacy has been rigorously validated through extensive testing. It was built and validated on over 8,800 MRI images, with further development on over 15,000 cardiac MRI images and validation on a separate set of over 7,700 images. An additional out-of-distribution test on 1,125 knee MRI images, which the system had never encountered, demonstrated up to 75 percent shorter scans while outperforming state-of-the-art models in both speed and image quality. A blinded assessment with a consultant radiologist at Buckinghamshire Healthcare NHS Trust in the UK confirmed that GenMRI-enhanced images were diagnostically equivalent to conventional MRI images, with technical evaluations showing up to 99.7 percent similarity.
Mary-Brenda Akoda's Vision
Mary-Brenda Akoda, a UK-based Nigerian artificial intelligence research scientist and founder of GenScan AI, is the driving force behind GenMRI. Her impressive background includes being a Google DeepMind Scholar, an ex-Microsoft engineer, and an Imperial College London-trained researcher. Akoda's inspiration for this innovation stems from a deeply personal experience: the loss of an elderly loved one due to delays in timely imaging for a stroke, compounded by her own encounters with slow hospital processes. This personal tragedy underscored the critical importance of rapid diagnosis in time-sensitive conditions like stroke and cancer, where every second can be the difference between life and death.
Akoda's plan is to roll out GenMRI in Nigeria and the UK by the second half of 2027. This strategic launch aims to address the global challenge of overburdened health systems and patient backlogs. Her vision extends beyond mere efficiency, seeking to fundamentally transform how medical imaging is conducted, making it more accessible and responsive to urgent patient needs. By leveraging AI, she hopes to mitigate the human cost associated with diagnostic delays, which she notes contribute to millions of deaths annually from conditions like stroke and cancer.
Transforming Patient Care
The introduction of GenMRI promises a significant transformation in patient care by directly tackling several persistent issues within healthcare systems. By drastically cutting MRI scan times, hospitals and imaging centers can accommodate substantially more patients daily, effectively shortening lengthy waiting lists. This increased capacity is particularly beneficial for vulnerable populations such as elderly patients, children, and infants, who often require sedation for prolonged scans. The reduction in scan duration also minimizes the need for sedation and repeat scans, which can occur if patients move during the lengthy process, leading to blurry images.
Furthermore, the technology's ability to provide faster diagnoses is critical for time-sensitive conditions. The article highlights that stroke kills over 6.5 million people yearly and cancer over 10 million, with medical imaging often being the crucial first step to diagnosis. GenMRI's speed can ensure that patients with such conditions receive timely assessments, potentially leading to earlier intervention and improved survival rates. This innovation not only enhances operational efficiency but also directly contributes to better patient outcomes and a more responsive healthcare infrastructure, particularly in regions like Nigeria where healthcare resources are often stretched.
Key points
- Nigerian AI scientist Mary-Brenda Akoda developed GenMRI, an AI software that cuts MRI scan times by up to 90 percent.
- GenMRI can reduce a 20-minute scan to two minutes and an hour-long scan to six minutes on existing MRI machines.
- The technology was validated on over 8,800 MRI images and assessed as diagnostically equivalent to conventional MRI by a UK radiologist.
- Akoda's inspiration came from personal loss due to diagnostic delays in an overburdened health system.
- GenMRI is slated for rollout in Nigeria and the UK by the second half of 2027, aiming to reduce patient backlogs and improve timely diagnosis for critical conditions.
The rollout of GenMRI could revolutionize medical diagnostics, significantly reducing patient waiting times and improving access to critical imaging services globally, especially in regions with strained healthcare infrastructure. Faster diagnoses for conditions like stroke and cancer could lead to earlier treatment and save millions of lives annually, showcasing African innovation's potential to address global health challenges.
