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Proceedings Paper

The wearable augmented reality (AR) approach to support mammographic training: hololens for screener training
Author(s): Qiang Tang; Yan Chen; Gerald Schaefer; Alastair Gale
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Paper Abstract

Screening training efficiency highly relies on appropriate interaction and feedbacks provided during training.1,2 A dedicated screening workstation and dedicated viewing software are de rigour for UK breast cancer screener training. These workstation and software are mainly manufactured by leading international vendors without critical technical aspects divulged to allow integrating 3rd party screener training solutions. A non-wearable AR approach has been developed and its accuracy has been quantitatively identified. As a follow-up, this study has refactored previous approaches on the wearable platform, Hololens. Wearable AR solutions are considerably user-friendly in degrees of freedom movements whilst they are seamlessly integrated and less customisable. It has not been aware that screening-suitable room-scale AR approaches have been developed and adopted. However, wearable AR techniques have relatively sophisticated apparatus developed for personal usage. In this study, Hololens is adopted and the difficulties of employing wearable AR techniques on screening training are systematically addressed. It is found infrared sensors of wearable AR solutions cannot retrieve spacious data correctly in the real world while the detected object is a monitor screen or other infrared-relative objects. Moreover, Hololens has the difficulty of detecting large objects and its interaction range and visible ranges are both quite limited. Whereas an alternative method is developed for Hololens and it is fully functional for screening training.

Paper Details

Date Published: 15 March 2019
PDF: 8 pages
Proc. SPIE 10954, Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications, 1095408 (15 March 2019); doi: 10.1117/12.2512425
Show Author Affiliations
Qiang Tang, Loughborough Univ. (United Kingdom)
Yan Chen, Loughborough Univ. (United Kingdom)
Gerald Schaefer, Loughborough Univ. (United Kingdom)
Alastair Gale, Loughborough Univ. (United Kingdom)

Published in SPIE Proceedings Vol. 10954:
Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications
Po-Hao Chen; Peter R. Bak, Editor(s)

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