posted on 2018-04-10, 09:24authored byQiang 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.
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