Forced choice and ordinal discrete rating assessment of image quality: A comparison

This study compared a five-category ordinal scale and a two-alternative forced-choice subjective rating of image quality preferences in a multiabnormality environment. 140 pairs of laser-printed posteroanterior (PA) chest images were evaluated twice by three radiologists who were asked to select during a side-by-side review which image in each pair was the “better” one for the determination of the presence or absence of specific abnormalities. Each pair included one image (the digitized film at 100 μm pixel resolution and laser printed onto film) and a highly compressed (∼60∶1) and decompressed version of the digitized film that was laser printed onto film. Ratings were performed once with a five-category ordinal scale and once with a two-alternative forced-choice scale. The selection process was significantly affected by the rating scale used. The “comparable” or “equivalent for diagnosis” category was used in 88.5% of the ratings with the ordinal scale. When using the two-alternative forced-choice approach, noncompressed images were selected 66.8% of the time as being the “better” images. This resulted in a significantly lower ability to detect small differences in perceived image quality between the noncompressed and compressed images when the ordinal rating scale is used. Observer behavior can be affected by the type of question asked and the rating scale used. Observers are highly sensitive to small differences in image presentation during a side-by-side review.

[1]  C A Britton,et al.  Digital radiography and conventional imaging of the chest: a comparison of observer performance. , 1994, AJR. American journal of roentgenology.

[2]  H E Rockette,et al.  The effect of image processing on chest radiograph interpretations in a PACS environment. , 1990, Investigative radiology.

[3]  I. Bodis-Wollner,et al.  Visual contrast sensitivity , 1988, Neurology.

[4]  David Gur,et al.  Effect of experimental design on sample size , 1991, Medical Imaging.

[5]  H E Rockette,et al.  The use of continuous and discrete confidence judgments in receiver operating characteristic studies of diagnostic imaging techniques. , 1992, Investigative radiology.

[6]  Norman B. Nill,et al.  A Visual Model Weighted Cosine Transform for Image Compression and Quality Assessment , 1985, IEEE Trans. Commun..

[7]  C E Metz,et al.  Some practical issues of experimental design and data analysis in radiological ROC studies. , 1989, Investigative radiology.

[8]  C A Britton,et al.  Selection of processing algorithms for digital image compression: a rank-order study. , 1995, Academic radiology.

[9]  D. H. Kelly Visual Contrast Sensitivity , 1977 .

[10]  David Gur,et al.  Subjective and objective assessment of image quality—A comparison , 1994, Journal of Digital Imaging.

[11]  M. A. Hamdan,et al.  Maximum likelihood estimation of the parameters of the bivariate binomial distribution , 1986 .

[12]  D. R. Jensen,et al.  A BIVARIATE BINOMIAL DISTRIBUTION AND SOME APPLICATIONS1 , 1976 .

[13]  David Gur,et al.  Subjective quality assessment of computed radiography hand images , 2009, Journal of Digital Imaging.

[14]  H E Rockette,et al.  Effect of observer instruction on ROC study of chest images. , 1990, Investigative radiology.

[15]  David Gur,et al.  Joint Photographic Experts Group (JPEG) compatible data compression of mammograms , 1994, Journal of Digital Imaging.

[16]  King Ngi Ngan,et al.  Cosine Transform Coding Incorporating Human Visual System Model , 1986, Other Conferences.

[17]  R C Zepp,et al.  Simple steps for improving multiple-reader studies in radiology. , 1996, AJR. American journal of roentgenology.