Thoracic CT images: effect of lossy image compression on diagnostic accuracy.
OBJECTIVE
To evaluate the effects of lossy image (noninvertible) compression on diagnostic accuracy of thoracic computed tomographic images.


METHODS
Sixty images from patients with mediastinal adenopathy and pulmonary nodules were compressed to six different levels with tree-structured vector quantization. Three radiologists then used the original and compressed images for diagnosis. Unlike many previous receiver operating characteristic-based studies that used confidence rankings and binary detection tasks, this study examined the sensitivity and predictive value positive scores from nonbinary detection tasks.


RESULTS
At the 5% significance level, there was no statistically significant difference in diagnostic accuracy of image assessment at compression rates of up to 9:1.


CONCLUSIONS
The techniques presented for evaluation of image quality do not depend on the specific compression algorithm and provide a useful approach to evaluation of the benefits of any lossy image processing technique.
Cosman
P C
PC
Department of Electrical Engineering, Stanford University, CA 94305-4055.
Davidson
H C
HC
Bergin
C J
CJ
Tseng
C W
CW
Moses
L E
LE
Riskin
E A
EA
Olshen
R A
RA
Gray
R M
RM
D006801:Humans; D007091:Image Processing, Computer-Assisted; D008168:Lung / Q000000981:diagnostic imaging; D008482:Mediastinum / Q000000981:diagnostic imaging; D011237:Predictive Value of Tests; D013902:Radiography, Thoracic; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed