EVALUATION OF A COMBINED 2-DIMENSIONAL AND 3-DIMENSIONAL COMPRESSION METHOD USING HUMAN VISUAL CHARACTERISTICS TO YIELD HIGH-QUALITY 10 1-COMPRESSION OF CRANIAL COMPUTED-TOMOGRAPHY SCANS/

RATIONALE AND OBJECTIVES. The compression of cranial computed tomograp hy scans was improved by using independent intra- and interframe compr ession techniques. METHODS. For intraframe compression, an image was d ecomposed 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 q uantizer (CVQ) based on human visual perception characteristics. Inter frame redundancy is exploited by a displacement estimated interslice ( DEI) algorithm that encodes the differences between reference subimage s from adjacent slices. This combined DEI/CVQ method was subjectively evaluated by 13 radiologists under a blinded protocol, and was compare d to the CVQ method alone, the DEI method alone, the original images, and to a standard intraframe discrete cosine transform (DCT) compressi on method. RESULTS. Only the combined DEI/CVQ method at 10:1 compressi on 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 intrafr ame redundancy, and by modeling some characteristics of human visual p erception. The DEI/CVQ method is well-suited for progressive transmiss ion, and thus, holds potential in teleradiology as well as picture arc hiving and communications systems.