Investigation of optimal display size for viewing T1‐weighted MR images of the brain using a digital contrast‐detail phantom

Abstract

We clarified the relationship between the display size of MRI images and observer performance using a digital contrast‐detail (d‐CD) phantom. The d‐CD phantom was developed using Microsoft Visual Basic 2010 Express. It had a 512×512 matrix in size and a total of 100 holes, whose diameter increased stepwise from 4 to 40 pixels with a 4‐pixel interval in the vertical direction; the contrast varied stepwise in the horizontal direction. The digital driving level (DDL) of the background, the width of the DDL, and the contrast were adjustable. These parameters were determined on the basis of the actual T1‐weighted magnetic resonance (MR) images of the brain. In this study, the DDL, width, and contrast were set to 85, 20, and 1, respectively. The observer performance study was performed for three different display sizes (30 cm×30 cm as the enlarged size, 16 cm×16 cm as the original size, and 10 cm×10 cm as the reduced size) using a 2‐megapixel color liquid crystal display monitor, and it was analyzed using Friedman and Wilcoxon statistical tests. The observer performances for the original display false(p<0.01false) and the reduced display sizes false(p<0.01false) were superior to that observed for the enlarged size, whereas there was no significant difference between the original display and reduced display sizes false(p=0.31false). Evaluation with the digital phantom simulating MR imaging also revealed that the original and reduced display sizes were superior to the enlarged display size in observer performance. The d‐CD phantom enables a short‐term evaluation of observer performance and is useful in analyzing relationship between display size and observer performance.PACS number: 87.57.‐s

Effects of body part thickness on low‐contrast detail detection and radiation dose during adult chest radiography

“…The advantages of using the CDRAD 2.0 phantom are that it makes it possible to thoroughly assess radiographic noise, sharpness and contrast. Improved IQF inv values in clinical practice could improve the identification of subtle diseases, for example, small lung nodules 14,15 . Moreover, a physical IQ method was used for calculating IQF inv using CDRAD 2.0 analyser software which offers high reliability and is unaffected by differences in human eyesight and experience 16 .…”

“…Improved IQF inv values in clinical practice could improve the identification of subtle diseases, for example, small lung nodules. 14,15 Moreover, a physical IQ method was used for calculating IQF inv using CDRAD 2.0 analyser software which offers high reliability and is unaffected by differences in human eyesight and experience. 16 The CDRAD 2.0 phantom and IQF inv measurements have been used widely for optimization studies and when comparing different DR detector types.…”