Nicholas Otumi is a biomedical imaging researcher and diagnostic imaging specialist affiliated with the University of Rochester, with expertise spanning diagnostic imaging, biomedical engineering, and artificial intelligence–driven medical image analysis. He holds a Master of Science in Diagnostic Imaging with specialization in bioengineering and biomedical engineering, and a Bachelor of Science in Diagnostic Imaging Technology, supported by advanced training in deep learning, signal processing, inverse problems, and clinical imaging. His professional experience includes research assistant roles across academic and clinical settings, where he has contributed to imaging model development, clinical data management, AI-based brain and chest image segmentation, and interdisciplinary healthcare research, alongside leadership and community engagement roles within university environments. His research focuses on medical image quality, user-centered imaging system evaluation, deep learning for disease classification, and the application of advanced MRI and CT techniques in both high- and low-resource settings, with multiple peer-reviewed journal publications and ongoing studies under review. He has received competitive research funding and fellowship recognition, institutional awards for leadership and versatility, and has participated in international scientific schools and specialized workshops in radiochemistry, medical physics, AI diagnostics, and imaging quality assurance. His academic service includes research collaboration, technical support, and scholarly dissemination, reflecting a strong commitment to advancing diagnostic imaging research and education.
Profiles: Google Scholar | ORCID
Featured Publications
AD Piersson, G Nunoo, E Tettey, N Otumi, User-centered assessment of MRI equipment flexibility, workspace adequacy, user interface usability, and technical proficiency. Appl. Clin. Inform., 2025, 16(5), 1595–1605.
AD Piersson, G Nunoo, K Dzefi-Tettey, N Otumi, Utility of advanced brain MRI techniques for clinical and research purposes in a low-resource setting: A multicentre survey. Next Res., 2025, 100638.
A Piersson, E Frost, K Dzefi-Tettey, N Otumi, H Mumuni, S Kafwimbi, et al., Public attitudes and preferences towards artificial intelligence in diagnostic imaging for clinical diagnosis in a low-resource setting (n = 1,032). Eur. Soc. Radiol. (ECR), 2025.
E Fiagbedzi, J Arkorful, IF Brobbey, E Appiah, S Nyarko, N Otumi, et al., A case of ruptured infrapatellar bursa sac with Baker’s cyst. Radiol. Case Rep., 2025, 20(1), 700–704.
E Fiagbedzi, J Arkorful, E Appiah, N Otumi, I Ofori, PN Gorleku, A rare case of intussusception in a 6-month-old baby. Radiol. Case Rep., 2025, 19(10), 4451–4456.