DocumentCode :
1676530
Title :
Scalar-vector quantization of medical images
Author :
Mohsenian, Nader ; Shahri, Homayount
Author_Institution :
IBM Corp., Endicott, NY, USA
Volume :
3
fYear :
1995
Firstpage :
1425
Abstract :
A new coding scheme based on the scalar-vector quantizer (SVQ) is developed for compression of medical images. SVQ is a fixed-rate encoder and its rate-distortion performance is close to that of optimal entropy-constrained scalar quantizers (ECSQ´s) for memoryless sources. For a set of magnetic resonance (MR) images, coding results obtained from SVQ and ECSQ at low bit-rates are indistinguishable. Furthermore, the authors´ encoded images are perceptually indistinguishable from the original, when displayed on a monitor. This makes the authors´ SVQ based coder an attractive compression scheme for picture archiving and communication systems (PACS), currently under consideration for an all digital radiology environment in hospitals, where reliable transmission, storage, and high fidelity reconstruction of images are desired
Keywords :
PACS; biomedical NMR; image coding; medical image processing; vector quantisation; digital radiology environment; encoded images; high fidelity image reconstruction; hospitals; magnetic resonance images; medical diagnostic imaging; medical images compression; memoryless sources; optimal entropy-constrained scalar quantizers; rate-distortion performance; reliable image storage; reliable image transmission; scalar-vector quantization; Biomedical imaging; Hospitals; Image coding; Image storage; Magnetic resonance; Monitoring; Picture archiving and communication systems; Quantization; Radiology; Rate-distortion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference Record, 1995., 1995 IEEE
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-3180-X
Type :
conf
DOI :
10.1109/NSSMIC.1995.500269
Filename :
500269
Link To Document :
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