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Rich interaction and feedback supported mammographic training: A trial of an augmented reality approach

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conference contribution
posted on 2018-04-10, 09:24 authored by Qiang TangQiang Tang, Yan Chen, Alastair G. Gale
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.

History

School

  • Science

Department

  • Computer Science

Published in

Communications in Computer and Information Science

Volume

723

Pages

377 - 385

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.

Publisher

© Springer

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2017

Notes

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

ISBN

9783319609638

ISSN

1865-0929

Book series

Communications in Computer and Information Science;723

Language

  • en

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