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Compression algorithms based on full-frame discrete cosine transforms have achieved compression ratios as high as 10:1 to 20:1 with almost imperceptible image degradation, when applied to projection radiographs digitized with 2,048 X 2,048 X 8-bit matrices. Compared with such radiographs, images obtained with computed tomography (CT) and magnetic resonance (MR) are smaller in size, have lower signal-to-noise ratios, and, in the case of CT, have a larger dynamic range. These differences result in qualitatively different spectral properties. The authors studied the efficiency of the full-frame technique when applied to CT and MR images. They achieved excellent results, with compression ratios in the neighborhood of 5:1. The study was performed with the use of a hardware implementation of the authors' algorithm, which can compress a 512 X 512 X 12-bit image in less than 1.5 seconds.

A hardware module was designed and built to implement the full-frame, bit-allocation image-compression algorithm in a clinical setting. The algorithm transforms an entire image without prepartitioning into small subimages. This adaptation eliminates block artifacts at subimage borders that can mimic relevant pathologic conditions. The quality of 1,024- and 2,048-pixel images compressed at a rate up to 10:1 with a custom-designed processor board (which contains four digital signal processors that transform and quantize separate rows and columns of an image independently with a two-pass cosine transform) and a 16-Mbyte frame buffer was found to be diagnostically acceptable in preliminary receiver operating characteristic studies. The module can compress a 1,024-pixel image in 4 seconds in a general-purpose computer system; images can be compressed in 1 second with the addition of a custom-designed data transporter. Copies of the compression module are being installed in the authors' department and in collaborating hospitals for laboratory and clinical evaluation.

We have established a three -dimensional (3 -D) imaging facility for reconstruction of serial two -dimensional (2 -D) ultrasound images.In the facility, contiguous 2 -D images are captured directly at the clinical site from the real -time video signals of a Labsonics serial ultrasound imager.The images are digitized and stored on an IBM PC. They are then transferred over an Ethernet communication network to the Image Processing Laboratory.Finally, the serial images are reformatted and the 3 -D images are reconstructed on a Pixar image computer.The reconstruction method involves grey level remapping, slice interpolation, tissue classification, surface enhancement, illumination, projection, and display.We have demonstrated that 3 -D ultrasound images can be created which bring out features difficult to discern in 2 -D ultrasound images.

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