Paper
13 July 1998 Clinical evaluation of high-performance lossless image compression
Anthony L. Daniell, Ming-Yuan Jin, Daniel J. Valentino
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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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Anthony L. Daniell, Ming-Yuan Jin, and Daniel J. Valentino "Clinical evaluation of high-performance lossless image compression", Proc. SPIE 3339, Medical Imaging 1998: PACS Design and Evaluation: Engineering and Clinical Issues, (13 July 1998); https://doi.org/10.1117/12.319798
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KEYWORDS
Image compression

Image processing

Chest

Computed tomography

Picture Archiving and Communication System

Abdomen

Brain

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