Artificial intelligence in medical imaging : knowledge and perspectives of South African radiographers
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Abstract
Background: This study focused on determining the perspectives of Radiographers in
relation to the integration of AI into medical imaging. Artificial intelligence (AI) is the use
of technology and computers to replicate intelligent behaviours and analytical thoughts
that are similar to that of humans. Several studies indicate that medical imaging
professionals, such as Radiologists and Radiographers, are seeing an increase in the
use of AI applications in clinical settings. Diagnostic Radiographers are pivotal for the
integration of AI systems into medical imaging as they serve as an interface between
technology and patients. Although some studies have examined the perspectives of
Radiographers on AI in some African countries, there is still no clear picture of the
Radiographers’ perspectives towards AI in the most technologically advanced country in
Africa.
Aim of study: The study aimed to ascertain the knowledge and perspectives of South
African Radiographers regarding the integration of AI in diagnostic imaging in order to
provide unique recommendations to support the training of Radiographers.
Methodology: A quantitative cross-sectional research design was used. Non-probability
purposive sampling was employed as it is the most appropriate approach for a content
analysis inquiry. A self-administered questionnaire containing closed-ended questions
was used to collect statistical data from Radiographers that statistical data from
Radiographers that met the requirements for participation. On completion of the
questionnaires, the results were tabulated and graphically demonstrated. Data was
analysed using the latest version 27 of SPSS (the Statistical Package for the Social
Sciences).
Findings: SPSS version 27 was used to analyse the data and various statistical tests
such as Descriptive statistics, the Analysis of Variance Model, the Binomial test,
Pearson's correlation coefficient, One-sample t-test, Cronbach alpha and Independent
samples t-test were adopted to analyse the data yielded by the collection tool. The
findings indicated that over 90 % of Radiographers in South Africa are aware of the
concept of AI. The majority of Radiographers in South Africa have a positive attitude
towards AI as there was significant agreement that AI is beneficial to the various aspects
of diagnostic Radiography. While AI possesses many benefits, Radiographers also
acknowledge the various barriers affecting the implementation of AI in the medical
imaging profession.
Conclusion: It can be concluded that Radiographers recognize general AI concepts and
are aware of some of AI’s functional roles within the field but are unfamiliar with the more
technical components of the technology. Therefore, the introduction of AI in the
Radiography curriculum is pivotal to ensuring that Radiographers have a strong
foundation for understanding AI. It was noted that Radiographers in South Africa believe
that AI will have multiple benefits for their job performance. Inasmuch as AI is equipped
with benefits for Radiographers, several barriers that hinder the implementation of AI in
Radiography were also noted.
Description
A dissertation submitted in fulfilment of the requirements for the Degree of Master of Health Sciences in Radiography at the Durban University of Technology, Durban, South Africa, 2026.
Citation
DOI
https://doi.org/10.51415/10321/6493
