Medical image compression with set partitioning in hierarchical trees

Author

Manduca, Armando

Author_Institution

Dept. of Physiol. & Biophys., Mayo Clinic & Found., Rochester, MN, USA

Volume

3

fYear

1996

fDate

31 Oct-3 Nov 1996

Firstpage

1224

Abstract

Wavelet-based image compression is proving to be a very effective technique for medical images, giving significantly better results than the JPEG algorithm. A novel scheme for encoding wavelet coefficients, termed set partitioning in hierarchical trees, has recently been proposed and yields significantly better compression than more standard methods. The authors report the results of experiments comparing such coding to more conventional wavelet compression and to JPEG compression on several types of medical images

Keywords

data compression; medical image processing; set theory; trees (mathematics); wavelet transforms; JPEG algorithm; PACS; hierarchical trees; medical diagnostic imaging; medical image compression; set partitioning; teleradiology; wavelet coefficients encoding; wavelet-based image compression; Biomedical imaging; Biophysics; Discrete wavelet transforms; Image coding; Physiology; Quantization; Sequences; Transform coding; Wavelet coefficients; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE

Conference_Location

Amsterdam

Print_ISBN

0-7803-3811-1

Type

conf

DOI

10.1109/IEMBS.1996.652783

Filename

652783