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Proceedings Paper

Luminance level of a monitor: influence on detectability and detection rate of breast cancer in 2D mammography
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Paper Abstract

Purpose: To evaluate lesion detectability and reading time as a function of luminance level of the monitor. Material and Methods: 3D mass models and microcalcification clusters were simulated into ROIs of for processing mammograms. Randomly selected ROIs were subdivided in three groups according to their background glandularity: high (>30%), medium (15-30%) and low (<15%). 6 non-spiculated masses (9 – 11mm), 6 spiculated masses (5 – 7mm) and 6 microcalcification clusters (2 – 4mm) were scaled in 3D to create a range of sizes. The linear attenuation coefficient (AC) of the masses was adjusted from 100% glandular tissue to 90%, 80%, 70%, to create different contrasts. Six physicists read the full database on Barco’s Coronis Uniti monitor for four different luminance levels (300, 800, 1000 and 1200 Cd/m2), using a 4-AFC tool. Percentage correct (PC) and time were computed for all different conditions. A paired t-test was performed to evaluate the effect of luminance on PC and time. A multi-factorial analysis was performed using MANOVA.. Results: Paired t-test indicated a statistically significant difference for the average time per session between 300 and 1200; 800 and 1200; 1000 and 1200 Cd/m2, for all participants combined. There was no effect on PC. MANOVA denoted significantly lower reading times for high glandularity images at 1200 Cd/m2. Both types of masses were significantly faster detected at 1200 Cd/m2, for the contrast study. In the size study, microcalcification clusters and spiculated masses had a significantly higher detection rate at 1200 Cd/m2. Conclusion: These results demonstrate a significant decrease in reading time, while detectability remained constant.

Paper Details

Date Published: 24 March 2016
PDF: 9 pages
Proc. SPIE 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 97870Y (24 March 2016); doi: 10.1117/12.2216472
Show Author Affiliations
Frédéric Bemelmans, KU Leuven (Belgium)
Alaleh Rashidnasab, KU Leuven (Belgium)
Univ. College London (United Kingdom)
Frédérique Chesterman, Barco N.V. (Belgium)
Tom Kimpe, Barco N.V. (Belgium)
Hilde Bosmans, UZ Leuven (Belgium)

Published in SPIE Proceedings Vol. 9787:
Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Matthew A. Kupinski, Editor(s)

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