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Related Experiment Videos

A segmentation-based lossless image coding method for high-resolution medical image compression

L Shen1, R M Rangayyan

  • 1Department of Electrical and Computer Engineering, University of Calgary, Alta, Canada.

IEEE Transactions on Medical Imaging
|June 1, 1997
PubMed
Summary
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A new segmentation-based lossless image coding (SLIC) method improves medical image compression. This technique achieves better lossless compression ratios compared to existing methods for chest and breast images.

Area of Science:

  • Medical Imaging
  • Image Compression
  • Computer Vision

Background:

  • Lossless compression is critical for medical image archival and communication.
  • Existing methods may not offer optimal compression ratios for diverse medical image datasets.

Purpose of the Study:

  • To introduce a novel segmentation-based lossless image coding (SLIC) method.
  • To evaluate the performance of SLIC against established image compression techniques.

Main Methods:

  • Developed a SLIC method utilizing a region growing procedure for adaptive scanning.
  • Generated a discontinuity index map and an error image with a small dynamic range.
  • Encoded data using the Joint Bi-level Image experts Group (JBIG) standard.

Main Results:

Related Experiment Videos

  • Achieved average lossless compression ratios of 1.6 bits/pixel (from 8 bits) and 2.9 bits/pixel (from 10 bits).
  • Demonstrated superior performance over JBIG, JPEG, HINT, and Burg Prediction methods by 4% to 28% on a chest and breast image database.

Conclusions:

  • The SLIC method offers significant improvements in lossless compression for medical images.
  • SLIC provides a more efficient alternative for medical image archival and transmission.