Optimization of a contrast-detail-based method for electronic image display quality evaluation

Hangiandreou, Nicholas J.; Fetterly, Kenneth A.; Felmlee, Joel P.

doi:10.1007/bf03168844

Cited by 10 publications

(4 citation statements)

References 16 publications

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“…In this paper the concept of an ideal observer 13 is used in an effort to obtain ideal CDMAM phantom scoring and applied to compare different published methodologies and parameters. 2,[4][5][6][7][8][9] In principle, the concept which has been developed can be applied to any type of Rose contrast-detail phantom. In the light of the developed concept, the application of the CDMAM phantom for evaluation of the digital mammography system is considered.…”

Section: Introductionmentioning

confidence: 99%

Contrast‐detail phantom scoring methodology

et al. 2005

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Published results of medical imaging studies which make use of contrast detail mammography (CDMAM) phantom images for analysis are difficult to compare since data are often not analyzed in the same way. In order to address this situation, the concept of ideal contrast detail curves is suggested. The ideal contrast detail curves are constructed based on the requirement of having the same product of the diameter and contrast (disk thickness) of the minimal correctly determined object for every row of the CDMAM phantom image. A correlation and comparison of five different quality parameters of the CDMAM phantom image determined for obtained ideal contrast detail curves is performed. The image quality parameters compared include: (1) contrast detail curve--a graph correlation between "minimal correct reading" diameter and disk thickness; (2) correct observation ratio--the ratio of the number of correctly identified objects to the actual total number of objects multiplied by 100; (3) image quality figure--the sum of the product of the diameter of the smallest scored object and its relative contrast; (4) figure-of-merit--the zero disk diameter value obtained from extrapolation of the contrast detail curve to the origin (e.g., zero disk diameter); and (5) k-factor--the product of the thickness and the diameter of the smallest correctly identified disks. The analysis carried out showed the existence of a nonlinear relationship between the above parameters, which means that use of different parameters of CDMAM image quality potentially can cause different conclusions about changes in image quality. Construction of the ideal contrast detail curves for CDMAM phantom is an attempt to determine the quantitative limits of the CDMAM phantom as employed for image quality evaluation. These limits are determined by the relationship between certain parameters of a digital mammography system and the set of the gold disks sizes in the CDMAM phantom. Recommendations are made on selections of CDMAM phantom regions which should be used for scoring at different image quality and which scoring methodology may be most appropriate. Special attention is also paid to the use of the CDMAM phantom for image quality assessment of digital mammography systems particularly in the vicinity of the Nyquist frequency.

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Section: Introductionmentioning

confidence: 99%

Contrast‐detail phantom scoring methodology

et al. 2005

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“…To evaluate the effect of changes in CRT monitor luminance on the detection performance, the image-reading [9], and the design for test images was analogous to the contrast-detail method proposed by Hangiandreou et al [10,11]. The luminance changes in CRT monitor displays were the same as in our previous study, and were the ones in which the grid voltage was decreased [8].…”

Section: Methodsmentioning

confidence: 99%

Effects of monitor luminance change on observer detection performance

Hidano

Ikeda

Ishigaki

et al. 2005

Computerized Medical Imaging and Graphics

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“…The study used a well-established method for evaluating the performance of imaging systems, 8,[10][11][12][13][14][15][16][17] including medical displays. 18,19 Compared to prior work on the low-contrast detectability of displays, the hallmarks of the current study are the use of ͑1͒ digital radiography images with representative radiographic quantum noise backgrounds, ͑2͒ an automated graphical user interface ͑GUI͒ providing efficient use of the observer's time, and ͑3͒ a new statistical analysis of the observer scores for contrast-detail data.…”

Section: Introductionmentioning

confidence: 99%

A comparative contrast‐detail study of five medical displaysa)

2008

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The objective of this study was to compare the contrast-detail performance of five different commercial liquid crystal displays (LCDs) to other LCD and cathode-ray tube (CRT) displays for medical applications. A contrast-detail phantom, supplemented with 5 in. of acrylic, was imaged on a commercial digital radiographic system using techniques comparable to chest radiography. The phantom design enabled observer evaluation by a four-alternative forced choice paradigm. The acquired images were independently scored by five observers on five medical display devices: a 5 megapixel monochrome LCD, a 3 megapixel monochrome LCD, a 9 megapixel color LCD, a 5 megapixel monochrome CRT, and a mammographic-grade monochrome CRT. The data were analyzed using the method suggested by the manufacturer based on a nearest neighbor correction technique. They were further analyzed using a logistic regression response model with a natural threshold using an overall chi-square test for display type followed by pairwise comparisons for individual display performance. The differences between the display devices were small. The standard analysis of the results based on the manufacturer-recommended method did not yield any statistically discernible trend among displays. The logistic regression analysis, however, indicated that the 5 megapixel monochrome LCD was statistically significantly (p <0.0001) superior to the others, followed by the 3 megapixel monochrome LCD (p<0.0001). The three other displays exhibited lower but generally similar performance characteristics. The findings suggest that 5 and 3 megapixel monochrome LCDs provide comparable but subtly superior contrast detectability than other tested displays, with the former performing slightly better in the detection of subtle and fine details.

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Optimization of a contrast-detail-based method for electronic image display quality evaluation

Cited by 10 publications

References 16 publications

Contrast‐detail phantom scoring methodology

Contrast‐detail phantom scoring methodology

Effects of monitor luminance change on observer detection performance

A comparative contrast‐detail study of five medical displaysa)

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