Paper
18 May 2000 Integrating JPEG compression with DICOM: experiences and technical issues
Norbert H. Olges, Marco Eichelberg, Joerg Riesmeier, Peter F. Jensch
Author Affiliations +
Abstract
The exchange of medical images over networks or storage media is usually done in DICOM format today. In addition to uncompressed image storage, DICOM supports both lossless and lossy image compression techniques. Whereas lossless compression is popular for some applications, lossy compression in DICOM has never gained intensive usage. However, the quickly rising data volumes produced by the latest generation of modalities indicate that compression will remain an important issue although network bandwidth and storage capacities are increasing as well. The study presented in this contribution examines the conditions under which existing uncompressed DICOM images can be compressed with lossless and lossy JPEG resulting in valid DICOM images. The aim of the study was to enhance an existing open-source DICOM toolkit with JPEG support such that a wide range of DICOM images can be processed. Since image compression is not an integral part of the DICOM data model, its introduction can lead to surprising conflicts, e.g. because the special requirements of certain modalities do not match the JPEG model or because ambiguities in the standard are interpreted differently by different implementers. The resolution of the existing ambiguities could help to make DICOM image compression more robust in the future.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Norbert H. Olges, Marco Eichelberg, Joerg Riesmeier, and Peter F. Jensch "Integrating JPEG compression with DICOM: experiences and technical issues", Proc. SPIE 3980, Medical Imaging 2000: PACS Design and Evaluation: Engineering and Clinical Issues, (18 May 2000); https://doi.org/10.1117/12.386440
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KEYWORDS
Image compression

Image quality

Medical imaging

RGB color model

Computer programming

Image resolution

Image storage

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