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Deng, S.* ; Wheeler, G.* ; Toussaint, N.* ; Munroe, L.* ; Bhattacharya, S.* ; Sajith, G.* ; Lin, E.* ; Singh, E.* ; Chu, K.Y.K.* ; Kabir, S.* ; Pushparajah, K.* ; Simpson, J.M.* ; Schnabel, J.A. ; Gomez, A.*

A virtual reality system for improved image-based planning of complex cardiac procedures.

J. Imaging 7:151 (2021)
Publ. Version/Full Text DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
The intricate nature of congenital heart disease requires understanding of the complex, patient-specific three-dimensional dynamic anatomy of the heart, from imaging data such as three-dimensional echocardiography for successful outcomes from surgical and interventional procedures. Conventional clinical systems use flat screens, and therefore, display remains two-dimensional, which undermines the full understanding of the three-dimensional dynamic data. Additionally, the control of three-dimensional visualisation with two-dimensional tools is often difficult, so used only by imaging specialists. In this paper, we describe a virtual reality system for immersive surgery planning using dynamic three-dimensional echocardiography, which enables fast prototyping for visualisation such as volume rendering, multiplanar reformatting, flow visualisation and advanced interaction such as three-dimensional cropping, windowing, measurement, haptic feedback, automatic image orientation and multiuser interactions. The available features were evaluated by imaging and nonimaging clinicians, showing that the virtual reality system can help improve the understanding and communication of three-dimensional echocardiography imaging and potentially benefit congenital heart disease treatment.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Echocardiography ; Pre-operative Imaging ; Virtual Reality
ISSN (print) / ISBN 2313-433X
e-ISSN 2313-433X
Quellenangaben Volume: 7, Issue: 8, Pages: , Article Number: 151 Supplement: ,
Publisher MDPI
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute for Machine Learning in Biomed Imaging (IML)
Grants NIHR Invention for Innovation
Wellcome/EPSRC Centre for Medical Engineering
EPSRC Centre for Doctoral Training in Smart Medical Imaging