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Proceedings Paper

Eigen-Representations, Data Compression, And Transmission For Medical Images And Related Structures
Author(s): Paul R. Moran
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Paper Abstract

If any data compression scheme for medical images shows some level of success, then this necessarily implies information redundancy in the image data. The information capacity of the system therefore must be larger than the information content. A powerful way to analyze and exploit the possibilities for optimum data-compression, transmission methods, and other useful image-processing options is to seek the eigenfunction representation of the image. By transforming the image-data into the eigen-representation, we obtain a transformed image array (the q-space image) which is the irreducible representation of the data for that imaging system. The coefficients of the irreducible representation are, in the parlance of information theory, "non-interfering symbols". Preliminary studies show that the eigen-representation allows immediate, direct, and predictable compression of the system data capacity to the image data information content. Our analysis of medical images from magnetic resonance imaging (MRI) scans has allowed us to demonstrate some specific data-compression strategies which will be most beneficial, rapid and flexible for PACS applications

Paper Details

Date Published: 16 September 1985
PDF: 7 pages
Proc. SPIE 0536, 3rd Intl Conf on Picture Archiving and Communication Systems, (16 September 1985); doi: 10.1117/12.947355
Show Author Affiliations
Paul R. Moran, Wake Forest University (United States)


Published in SPIE Proceedings Vol. 0536:
3rd Intl Conf on Picture Archiving and Communication Systems
Samuel J. Dwyer; Robert J. Schneider, Editor(s)

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