Observer performance assessment of JPEG-compressed high-resolution chest images

The JPEG compression algorithm was tested on a set of 529 chest radiographs that had been digitized at a spatial resolution of 100 micrometer and contrast sensitivity of 12 bits. Images were compressed using five fixed 'psychovisual' quantization tables which produced average compression ratios in the range 15:1 to 61:1, and were then printed onto film. Six experienced radiologists read all cases from the laser printed film, in each of the five compressed modes as well as in the non-compressed mode. For comparison purposes, observers also read the same cases with reduced pixel resolutions of 200 micrometer and 400 micrometer. The specific task involved detecting masses, pneumothoraces, interstitial disease, alveolar infiltrates and rib fractures. Over the range of compression ratios tested, for images digitized at 100 micrometer, we were unable to demonstrate any statistically significant decrease (p greater than 0.05) in observer performance as measured by ROC techniques. However, the observers' subjective assessments of image quality did decrease significantly as image resolution was reduced and suggested a decreasing, but nonsignificant, trend as the compression ratio was increased. The seeming discrepancy between our failure to detect a reduction in observer performance, and other published studies, is likely due to: (1) the higher resolution at which we digitized our images; (2) the higher signal-to-noise ratio of our digitized films versus typical CR images; and (3) our particular choice of an optimized quantization scheme.

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

[2]  Hugh D. Curtin,et al.  Primary diagnosis of chest images in a PACS environment , 1990, Medical Imaging.

[3]  David Gur,et al.  Pixel averaging versus digitization using larger apertures: a comparison of the spatial resolution properties , 1992, Medical Imaging.

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

[5]  G G Cox,et al.  The effects of lossy compression on the detection of subtle pulmonary nodules. , 1996, Medical physics.

[6]  S Sakuma,et al.  Clinical evaluation of irreversible image compression: analysis of chest imaging with computed radiography. , 1990, Radiology.

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

[8]  K. Berbaum,et al.  Receiver operating characteristic rating analysis. Generalization to the population of readers and patients with the jackknife method. , 1992, Investigative radiology.

[9]  M L Giger,et al.  Data compression: effect on diagnostic accuracy in digital chest radiography. , 1991, Radiology.

[10]  H K Huang,et al.  The Effect of Irreversible Image Compression on Diagnostic Accuracy in Thoracic Imaging , 1993, Investigative radiology.

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