Share Email Print
cover

Proceedings Paper

High throughput screening for mammography using a human-computer interface with rapid serial visual presentation (RSVP)
Author(s): Chris Hope; Annette Sterr; Premkumar Elangovan; Nicholas Geades; David Windridge; Ken Young; Kevin Wells
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

The steady rise of the breast cancer screening population, coupled with data expansion produced by new digital screening technologies (tomosynthesis/CT) motivates the development of new, more efficient image screening processes. Rapid Serial Visual Presentation (RSVP) is a new fast-content recognition approach which uses electroencephalography to record brain activity elicited by fast bursts of image data. These brain responses are then subjected to machine classification methods to reveal the expert’s ‘reflex’ response to classify images according to their presence or absence of particular targets. The benefit of this method is that images can be presented at high temporal rates (~10 per second), faster than that required for fully conscious detection, facilitating a high throughput of image (screening) material. In the present paper we present the first application of RSVP to medical image data, and demonstrate how cortically coupled computer vision can be successfully applied to breast cancer screening. Whilst prior RSVP work has utilised multichannel approaches, we also present the first RSVP results demonstrating discriminatory response on a single electrode with a ROC area under the curve of 0.62- 0.86 using a simple Fisher discriminator for classification. This increases to 0.75 – 0.94 when multiple electrodes are used in combination.

Paper Details

Date Published: 28 March 2013
PDF: 8 pages
Proc. SPIE 8673, Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment, 867303 (28 March 2013); doi: 10.1117/12.2007557
Show Author Affiliations
Chris Hope, Univ. of Surrey (United Kingdom)
Annette Sterr, Univ. of Surrey (United Kingdom)
Premkumar Elangovan, Univ. of Surrey (United Kingdom)
Nicholas Geades, Univ. of Surrey (United Kingdom)
David Windridge, Univ. of Surrey (United Kingdom)
Ken Young, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Kevin Wells, Univ. of Surrey (United Kingdom)


Published in SPIE Proceedings Vol. 8673:
Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Claudia R. Mello-Thoms, Editor(s)

© SPIE. Terms of Use
Back to Top