Clinical evaluation of high-performance lossless image compression
| Autor: | Anthony L. Daniell, Daniel J. Valentino, Ming-Yuan Jin |
|---|---|
| Rok vydání: | 1998 |
| Předmět: |
Lossless compression
business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Data_CODINGANDINFORMATIONTHEORY Picture archiving and communication system Compression ratio Medical imaging Medicine Computer vision Entropy encoding Artificial intelligence Computed radiography business Biomedical engineering Data compression Image compression |
| Zdroj: | SPIE Proceedings. |
| ISSN: | 0277-786X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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