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8 December 1995 Magnetic resonance image compression using scalar-vector quantization
Nader Mohsenian, Homayoun Shahri
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Proceedings Volume 2605, Coding and Signal Processing for Information Storage; (1995) https://doi.org/10.1117/12.228222
Event: Photonics East '95, 1995, Philadelphia, PA, United States
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 (ECSQs) for memoryless sources. The use of a fixed-rate quantizer is expected to eliminate some of the complexity issues of using variable-length scalar quantizers. When transmission of images over noisy channels is considered, our coding scheme does not suffer from error propagation which is typical of coding schemes which use variable-length codes. For a set of magnetic resonance (MR) images, coding results obtained from SVQ and ECSQ at low bit-rates are indistinguishable. Furthermore, our encoded images are perceptually indistinguishable from the original, when displayed on a monitor. This makes our 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.
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Nader Mohsenian and Homayoun Shahri "Magnetic resonance image compression using scalar-vector quantization", Proc. SPIE 2605, Coding and Signal Processing for Information Storage, (8 December 1995); https://doi.org/10.1117/12.228222
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KEYWORDS
Image compression
Quantization
Computer programming
Medical imaging
Magnetic resonance imaging
Image transmission
Picture Archiving and Communication System
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