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Proceedings Paper

Clinical evaluation of high-performance lossless image compression
Author(s): Anthony L. Daniell; Ming-Yuan Jin; Daniel J. Valentino
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Paper Abstract

Previously, we developed and implemented a lossless compression technique that provided a very high compression ratio for a variety of medical imaging modalities. We have extended our approach to satisfy additional requirements for the clinically acceptable implementation of lossless compression of digital medical images. Our new algorithm, called APC Codec (Rice) consists of a novel combination of techniques including adaptive prediction, Rice entropy coding, and multithreading. In order to demonstrate the clinical performance of our technique, we processed a large number of medical images (n greater than 10,000) obtained during the routine operation of the UCLA Clinical PACS. We report the resulting compression ratio and time statistics for different modalities and anatomies. The modalities tested were computed radiography (CR), magnetic resonance (MR), computed tomography (CT), and the anatomical regions included the brain, chest, abdomen and extremities. A comparison to the UNIX compress utility is provided as a performance benchmark.

Paper Details

Date Published: 13 July 1998
PDF: 13 pages
Proc. SPIE 3339, Medical Imaging 1998: PACS Design and Evaluation: Engineering and Clinical Issues, (13 July 1998); doi: 10.1117/12.319798
Show Author Affiliations
Anthony L. Daniell, UCLA School of Medicine (United States)
Ming-Yuan Jin, UCLA School of Medicine (United States)
Daniel J. Valentino, UCLA School of Medicine (United States)


Published in SPIE Proceedings Vol. 3339:
Medical Imaging 1998: PACS Design and Evaluation: Engineering and Clinical Issues
Steven C. Horii; G. James Blaine, Editor(s)

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