Title :
Medical image compression with set partitioning in hierarchical trees
Author :
Manduca, Armando
Author_Institution :
Dept. of Physiol. & Biophys., Mayo Clinic & Found., Rochester, MN, USA
fDate :
31 Oct-3 Nov 1996
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;
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
DOI :
10.1109/IEMBS.1996.652783