Rate My Professor Elio Arruzza

Elio Arruzza serves as a Lecturer in Medical Imaging within the School of Allied Health and Human Performance, College of Health at Adelaide University. Previously associated with the University of South Australia, he holds a Bachelor of Medical Radiation Science (Medical Imaging) earned from 2017 to 2020, a Master of Research in Health Sciences completed between 2021 and 2023 with a focus on the diagnostic accuracy of CT and ultrasound for acute appendicitis, and is currently pursuing a Doctor of Philosophy since 2023, investigating how Parkinson’s disease alters the appearance of specific brain regions. Complementing his academic appointments, Arruzza acts as the Stream Coordinator in Medical Imaging and maintains active clinical practice as a Medical Imaging Technologist in both private and public sectors across Adelaide, including ongoing roles with SA Health from 2025 and Jones Radiology from 2021.

Arruzza's academic interests center on artificial intelligence, image processing, health sciences, nuclear medicine, medical imaging, radiology, and organ imaging. His research aims to enhance patient outcomes via innovative medical imaging protocols and to advance medical imaging education, with particular emphasis on the application of artificial intelligence in clinical settings by health professionals. Notable publications include "Perceptions of pharmacology education and assessment among medical radiation science students at one Australian university: A cross-sectional survey" (Radiography, 2026, with Janetzki et al.), "Enriching surgical theatre competence through computer-based simulation" (Radiography, 2025), "23Na-MRI for breast cancer diagnosis and treatment monitoring: a scoping review" (Bioengineering, 2025, with Smith et al.), "Use of 360° interactive virtual tours to enhance familiarity of the radiology department" (Radiography, 2025, with Vu and Chau), "Perceptions and attitudes of health science students relating to artificial intelligence (AI): a scoping review" (Health Science Reports, 2024), and contributions to "Assessment of Standards for Reporting of Diagnostic Accuracy (STARD) 2015 guideline adherence in medical imaging diagnostic accuracy studies published in 2023" (Journal of Clinical Epidemiology, 2025). Through collaborations, particularly with Minh Chau, his work explores gamification, AI-driven educational tools, simulations, and virtual reality in radiography training.