Evaluation of a combined two- and three-dimensional compression method using human visual characteristics to yield high-quality 10:1 compression of cranial computed tomography scans.
OBJECTIVE
The compression of cranial computed tomography scans was improved by using independent intra- and interframe compression techniques.


METHODS
For intraframe compression, an image was decomposed into four subimages, one subimage was chosen as a reference subimage, and three of the subimages were predicted from the reference subimage. The prediction error was encoded with a classified vector quantizer (CVQ) based on human visual perception characteristics. Interframe redundancy is exploited by a displacement estimated interslice (DEI) algorithm that encodes the differences between reference subimages from adjacent slices. This combined DEI/CVQ method was subjectively evaluated by 13 radiologists under a blinded protocol, and was compared to the CVQ method alone, the DEI method alone, the original images, and to a standard intraframe discrete cosine transform (DCT) compression method.


RESULTS
Only the combined DEI/CVQ method at 10:1 compression was not scored significantly different from the original images. At 15:1 compression, the DEI/CVQ method was scored significantly better than the 10:1 DCT and any other 15:1 compression methods.


CONCLUSIONS
Compressed image quality is enhanced by exploiting inter- and intraframe redundancy, and by modeling some characteristics of human visual perception. The DEI/CVQ method is well-suited for progressive transmission, and thus, holds potential in teleradiology as well as picture archiving and communications systems.
Frank
M S
MS
Department of Radiology, University of Washington School of Medicine, Harborview Medical Center, Seattle 98104.
Lee
H
H
Kim
Y
Y
Rowberg
A H
AH
Lee
W
W
Riskin
E A
EA
D000704:Analysis of Variance; D006257:Head / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D015588:Observer Variation; D011856:Radiographic Image Enhancement; D011873:Radiology Information Systems; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014796:Visual Perception