Rahman Akinlusi, MD
Assistant Professor
Radiology
School of Medicine

Dr. Akinlusi’s research interests center on advancing nuclear medicine through theranostics, quantitative image analysis and the integration of artificial intelligence for improved diagnostic and therapeutic outcomes. He is passionate about developing and applying machine learning, deep learning, and computer-aided detection systems to enhance tumor response assessment, lesion characterization, and radiation dose optimization. Additionally, his work explores imaging informatics, such as secure data exchange, cloud-based clinical trial solutions, and federated learning to promote precision medicine and equitable access to advanced imaging technologies. A former high school science teacher, Dr. Akinlusi is dedicated to innovative teaching, curriculum development, simulation-based learning, and mentorship programs that foster diversity and patient education in nuclear medicine. He enjoys mentoring medical students and junior residents in nuclear and diagnostic radiology.