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Development of a novel 3D immersive visualisation tool for manual image matching

Published online by Cambridge University Press:  02 May 2019

B. Byrd
Affiliation:
Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GB, UK
M. Warren
Affiliation:
Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GB, UK
J. Fenwick
Affiliation:
Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GB, UK
P. Bridge*
Affiliation:
Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GB, UK
*
Author for correspondence: P. Bridge, University of Liverpool, Brownlow Hill, Liverpool L69 3GB, UK. Tel: +44(0)1517958366. E-mail: pete.bridge@liverpool.ac.uk

Abstract

Aim:

The novel Volumetric Image Matching Environment for Radiotherapy (VIMER) was developed to allow users to view both computed tomography (CT) and cone-beam CT (CBCT) datasets within the same 3D model in virtual reality (VR) space. Stereoscopic visualisation of both datasets combined with custom slicing tools and complete freedom in motion enables alternative inspection and matching of the datasets for image-guided radiotherapy (IGRT).

Material and methods:

A qualitative study was conducted to explore the challenges and benefits of VIMER with respect to image registration. Following training and use of the software, an interview session was conducted with a sample group of six university staff members with clinical experience in image matching.

Results:

User discomfort and frustration stemmed from unfamiliarity with the drastically different input tools and matching interface. As the primary advantage, the users reported match inspection efficiency when presented with the 3D volumetric renderings of the planning and secondary CBCT datasets.

Findings:

This study provided initial evidence for the achievable benefits and limitations to consider when implementing a 3D voxel-based dataset comparison VR tool including a need for extensive training and the minimal interruption to IGRT workflow. Key advantages include efficient 3D anatomical interpretation and the capability for volumetric matching.

Type
Original Article
Copyright
© Cambridge University Press 2019 

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