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Title: Rich interaction and feedback supported mammographic training: A trial of an augmented reality approach
Authors: Tang, Qiang
Chen, Yan
Gale, Alastair G.
Keywords: Augmented reality
Mammographic training
Interaction
Feedback
Issue Date: 2017
Publisher: © Springer
Citation: TANG, Q., CHEN, Y. and GALE, A.G., 2017. Rich interaction and feedback supported mammographic training: A trial of an augmented reality approach. IN: Valdes Hernandez, M. and Gonzalez-Castro, V. (eds). Medical Image Understanding and Analysis, 21st Annual Conference, MIUA 2017, Edinburgh, UK, 11-13 July 2017, pp.377-385.
Series/Report no.: Communications in Computer and Information Science;723
Abstract: The conventional ‘keyboard and workstation’ approach allows complex medical image presentation and manipulation during mammographic interpretation. Nevertheless, providing rich interaction and feedback in real time for navigational training or computer assisted detection of disease remains a challenge. Through computer vision and state of the art AR (Augmented Reality) technique, this study proposes an ‘AR mammographic workstation’ approach which could support workstation-independent rich interaction and real-time feedback. This flexible AR approach explores the feasibility of facilitating various mammographic training scenes via AR as well as its limitations.
Description: This is a pre-copyedited version of a contribution published in Valdes Hernandez, M. and Gonzalez-Castro, V. (eds). Medical Image Understanding and Analysis, 21st Annual Conference, MIUA 2017 published by Springer. The definitive authenticated version is available online via https://doi.org/10.1007/978-3-319-60964-5_33
Version: Accepted for publication
DOI: 10.1007/978-3-319-60964-5_33
URI: https://dspace.lboro.ac.uk/2134/32519
Publisher Link: https://doi.org/10.1007/978-3-319-60964-5_33
ISBN: 9783319609638
ISSN: 1865-0929
Appears in Collections:Conference Papers and Presentations (Computer Science)

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