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Proceedings Paper

Compression of ultrasound images using wavelet-based space-frequency partitions
Author(s): Edwin Chiu; Jacques Vaisey; M. Stella Atkins
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Paper Abstract

This paper describes the compression of grayscale medical ultrasound images using a new compression technique, space- frequency segmentation. This method finds the rate- distortion optimal representation of an image from a large set of possible space-frequency partitions and quantizer combinations. The method is especially effective when the images to code are statistically inhomogeneous, which is the case for medical ultrasound images. We implemented a real compression algorithm based on this method, and applied the resulting algorithm to representation ultrasound images. The result is an effective technique that performs significantly better than a current leading wavelet transform coding algorithm, Set Partitioning In Hierarchical Trees (SPIHT), using the standard objective PSNR distortion measure. The performance of our space-frequency codec is illustrated, and the space-frequency partitions described. To obtain a qualitative measure of our method's performance, we describe an expert viewer study, where images compressed using both space-frequency compression and SPIHT were presented to ultrasound radiologists to obtain expert viewer assessment of the differences in quality between images from the two different methods. The expert viewer study showed the improved quality of space-frequency compressed images compared to SPIHT compressed images.

Paper Details

Date Published: 18 April 2000
PDF: 10 pages
Proc. SPIE 3976, Medical Imaging 2000: Image Display and Visualization, (18 April 2000); doi: 10.1117/12.383077
Show Author Affiliations
Edwin Chiu, Simon Fraser Univ. (Canada)
Jacques Vaisey, Simon Fraser Univ. (Canada)
M. Stella Atkins, Simon Fraser Univ. (Canada)


Published in SPIE Proceedings Vol. 3976:
Medical Imaging 2000: Image Display and Visualization
Seong Ki Mun, Editor(s)

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