Нигерийский учёный в США создал дешёвый ИИ для обнаружения опухолей мозга на обычных компьютерах

Campus Life Follow Us on GoogleJuly 16, 2026 by Damola Kola-Dare US-Based Nigerian scholar develops low-cost AI tool for brain tumour detection A United States-based Nigerian researcher, Oladele Ayomide Benjamen, has developed a low-cost artificial intelligence (AI) tool that could significantly improve brain tumour detection in hospitals and research institutions with limited computing resources, offering fresh hope for healthcare systems across developing countries. Benjamen, a doctoral student in Chemistry at Southern Methodist University, Texas, said the innovation was designed to make advanced medical AI accessible to institutions that cannot afford expensive computing infrastructure typically required for AI-powered medical imaging. His study, titled “Lightweight 3D U-Net for Brain Tumor Segmentation on CPUs: Enabling Deep Learning in Low-Resource Environments,” demonstrated that sophisticated AI models can accurately identify and map brain tumours using the Central Processing Unit (CPU) found in standard desktop and laptop computers, eliminating the need for costly Graphics Processing Units (GPUs). “My research is helping make medical AI more accessible, so that hospitals and researchers with limited resources are not left behind,” Benjamen said. The breakthrough comes amid growing global adoption of AI in cancer diagnosis. A 2025 systematic review and meta-analysis of 79 studies found that AI achieved an overall diagnostic accuracy of approximately 95.2 per cent in detecting and classifying brain tumours from MRI scans. Unlike conventional AI systems that depend on high-performance GPU-equipped computers, Benjamen’s model is optimised to run efficiently on CPUs, making it practical for hospitals in low-resource environments. A graduate of Obafemi Awolowo University, Ile-Ife, where he earned a Bachelor’s degree in Chemistry, Benjamen previously worked as a Biomedical AI Engineer at the Medical Artificial Intelligence (MAI) Laboratory in Lagos and also held AI and bioinformatics positions at DycoVue and Genomac. The CPU-based brain tumour project was conducted at MAI Lab alongside researchers, including Charity Umoren, under the supervision of the laboratory’s Executive Director, Dr. Maruf Adewole, with contributions from Prof. Fatade and Scientific Director at McGill University, Canada, Prof. Udunna. According to Benjamen, the research addresses a critical healthcare challenge in sub-Saharan Africa, where access to MRI facilities remains severely limited, with fewer than one MRI scanner available for every one million people. Even in centres equipped with MRI scanners, the high cost of computing infrastructure often prevents the deployment of advanced AI diagnostic systems. He explained that his lightweight deep-learning model removes this barrier by enabling hospitals to perform AI-assisted brain tumour analysis using conventional computers already available in many medical facilities. Beyond the CPU-based innovation, Benjamen also contributed to MAPS-Glioma, an international research collaboration involving scientists from Nigeria and Tanzania aimed at improving AI-assisted brain tumour analysis using medical imaging from resource-constrained environments. The project formed part of the international BraTS-Africa Challenge, where the research team ranked among the top-performing groups, earning recognition for the quality and relevance of its work. Speaking on his long-term vision, Benjamen said he hopes to combine artificial intelligence, chemistry, medical imaging and nanotechnology to develop practical healthcare solutions capable of improving diagnosis, treatment and patient outcomes. “My long-term goal is to combine technology and science to create solutions that are not only innovative but useful. By bringing together AI, chemistry and healthcare research, I hope to develop tools that improve lives, support medical progress and solve real societal problems,” he said. His doctoral research in the United States has also expanded into nanochemistry, where he is investigating nanocluster-based platforms that could support future advances in cancer diagnosis, therapy and biomedical materials. Commenting on the significance of the innovation, Raymond Confidence, Programme Chair of Spark Academy at McGill University, Canada, described the research as a major step toward democratizing AI-powered healthcare. Read Also: Team Nigeria: Igali lauds NSC welfare drive for Glasgow 2026 He said the technology would enable hospitals in Nigeria and other resource-limited countries to deploy deep-learning tools on standard computers, reducing dependence on expensive infrastructure while strengthening local capacity for AI-driven healthcare. Experts have, however, stressed that while AI continues to transform cancer diagnosis globally, the technology is intended to support—not replace—clinicians, with final diagnosis and treatment decisions remaining the responsibility of qualified medical professionals. Benjamen’s innovation adds to a growing body of global AI breakthroughs in oncology and underscores the increasing contribution of Nigerian researchers to developing affordable technologies capable of expanding access to quality healthcare in underserved communities.