Share Email Print

Proceedings Paper

A software tool to compare contrast-detail detection in uniform and in real mammographic backgrounds
Author(s): Gabriel Prieto; Margarita Chevalier; Eduardo Guibelalde
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

A software tool is presented to merge CDMAM phantom images with real mammographic backgrounds. It allows SKE tasks in uniform and in real backgrounds. This kind of tasks can be used to compare human, human visual metric or model observer performance in detail detection using uniform or mammographic backgrounds. As it is very well known, local characteristics of the structures in real mammographic backgrounds reduce the human performance in contrast-detail detection tasks. In consequence that performance cannot be inferred from the data acquired in white noise (flat) backgrounds such as a CDMAM phantom produces. It is of interest to compare the response of a mammography system to the same set of signals, either embedded in flat or in real backgrounds. This comparison achieves two goals. The first one is to analyze the variation of the recognition threshold of the system for both backgrounds. The second one is to analyze the performance of a human observer or a model observer over the same set of signals, varying the nature of the backgrounds. The software tool presented here uses CDMAM images to merge with a region of interest selected from a real mammography. This region as well as the mixing image method (basically adding or multiplying pixels) can be freely selected by the user. In this work a set of measurements of 8 images has been analyzed. We can preview the variation of the contrast-detail detection for a human observer and a human visual system metric (R*).

Paper Details

Date Published: 3 March 2011
PDF: 7 pages
Proc. SPIE 7966, Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment, 79661D (3 March 2011); doi: 10.1117/12.877460
Show Author Affiliations
Gabriel Prieto, Univ. Complutense de Madrid (Spain)
Margarita Chevalier, Univ. Complutense de Madrid (Spain)
Eduardo Guibelalde, Univ. Complutense de Madrid (Spain)

Published in SPIE Proceedings Vol. 7966:
Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment
David J. Manning; Craig K. Abbey, Editor(s)

© SPIE. Terms of Use
Back to Top