Visualise: an exploration of an artist's approach to 3-D computer visualisation in clinical radiology

Abstract

This doctoral thesis is a practice-led enquiry into the value of 3-D Computer Generated Imagery (CGI) in the visualisation and animation of clinical radiological scan data. The aim of this work is to develop an alternative pathway to visualising clinical data that augments and challenges the existing medical imaging aesthetic. It questions the integrity of the author?s arts-based interpretation of the radiological scan data and its relevance in the realworld context of enhancement of doctor-patient communication and interaction.The thesis starts by exploring current pathways for visualising the inner body, in particular biomedical animation, TV documentary, clinical 3-D visualisation and fine art practice inmedical imaging. This analysis is followed by an interrogation of the literature in the field of doctor-patient interaction, resulting in a small qualitative study with patients. This helps to define the opportunity for a new visualisation pathway that brings together the visual and narrative approaches of a 3-D computer animation aesthetic and the detail embedded inclinical radiological scan data.A multi-method approach is used to address the research questions. Informed by a collaborative two-year residency at Ninewells Hospital, NHS Tayside, Dundee, the author creates a series of 3-D CGI works that define this hybrid visualisation pathway. The resulting bandwidth of interpretative works is then investigated in a qualitative study involving semistructured interviews with professionals from the arts and clinical imaging. Overall, the study suggests that image integrity is tethered to context and purpose, contextualising the potential application of the author?s 3-D CGI works. The author concludes that his original contribution to knowledge is this alternative visualisation pathway, as developed through thebandwidth of interpretation. This is achieved through the exposition and use of the author?s tacit knowledge, and the collaborative approach. This provides a transferable model ofworking, for the future visualisation of medical scan data.

Date of Award	2009
Original language	English
Awarding Institution	University of Dundee
Supervisor	Nigel Johnson (Supervisor)