Paper
8 May 1989 Variable Rate Vector Quantization For Medical Image Compression With Applications To Progressive Transmission
Eve A. Riskin, Tom Lookabaugh, Philip A. Chou, Robert M. Gray
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Abstract
In this work, a new technique for variable rate VQ design based on tree structures is applied to medical images. It is an extension of an algorithm for optimal pruning in tree-structured classification and regression due to Breiman, Friedman, Olshen, and Stone [1]. The algorithm finds subtrees of a given tree-structured vector quantizer (TSVQ), each one optimal in that it has the lowest average distortion of all subtrees with the same or lesser average rate [2]. Since the resulting subtrees have variable height, natural variable rate coders result. Image reproduction at 1.5 bits per pixel is excellent and pathology in brain magnetic resonance images can be diagnosed in images at less than 0.5 bit per pixel. Finally, TSVQ is stored in a format convenient for progressive transmission of images.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Eve A. Riskin, Tom Lookabaugh, Philip A. Chou, and Robert M. Gray "Variable Rate Vector Quantization For Medical Image Compression With Applications To Progressive Transmission", Proc. SPIE 1091, Medical Imaging III: Image Capture and Display, (8 May 1989); https://doi.org/10.1117/12.976445
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Cited by 5 scholarly publications.
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KEYWORDS
Image compression

Medical imaging

Distortion

Image transmission

Quantization

Image quality

Digital imaging

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