Compression of ultrasound images using wavelet-based space-frequency partitions

Edwin Chiu; Jacques Vaisey; M. Stella Atkins

doi:10.1117/12.383077

18 April 2000 Compression of ultrasound images using wavelet-based space-frequency partitions

Edwin Chiu, Jacques Vaisey, M. Stella Atkins

Proceedings Volume 3976, Medical Imaging 2000: Image Display and Visualization; (2000) https://doi.org/10.1117/12.383077
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

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.

Citation Download Citation

Edwin Chiu, Jacques Vaisey, and M. Stella Atkins "Compression of ultrasound images using wavelet-based space-frequency partitions", Proc. SPIE 3976, Medical Imaging 2000: Image Display and Visualization, (18 April 2000); https://doi.org/10.1117/12.383077

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