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Proceedings Paper

Medical Image Sequence Coding Using Adaptive Vector Quantization
Author(s): Huifang Sun; Morris Goldberg
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Paper Abstract

A two-stage adaptive vector quantization scheme for radiographic image sequence coding is introduced. In vector quantization, an image se-quence is first mapped into a vector set; each vector is then encoded by two distinct pieces of information, the label and the corresponding code-word. The main problem in adaptive vector quantization is how to track the changes occurring in the sequence by updating the labels and the code-words. From the point of view of image vector quantization, the changes occurring in the radiographic image sequences can be categorized into two types: those due to body motion and those due to the injected contrast dye material. In the scheme proposed, encoding is performed in two stages. In the first stage, the label memory of the primary codebook is replenished to track the changes caused mainly by patient motions. In the second stage, the residual error vectors drawn from the area with contrast dye material are further encoded by a small secondary codebook. These areas are reliably detected as their mean values increase with the arrival of the contrast dye. By preferentially allocating extra bits (codewords) to these areas, both low distortion and better reproduction of the diagnostically useful information is obtained. Numerical and pictorial results are presented and demonstrate that good reproduction, especially those parts of the image containing contrast dye, can be obtained at a compression ratio of approximately 10 to 1 (about 0.8 bits/ pixel).

Paper Details

Date Published: 1 January 1987
PDF: 5 pages
Proc. SPIE 0767, Medical Imaging, (1 January 1987); doi: 10.1117/12.967007
Show Author Affiliations
Huifang Sun, Fairleigh Dickinson University (United States)
Morris Goldberg, University of Ottawa (Canada)

Published in SPIE Proceedings Vol. 0767:
Medical Imaging
Samuel J. Dwyer III; Roger H. Schneider, Editor(s)

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