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Related Experiment Videos

Compression and reconstruction of sorted PET listmode data.

S Vandenberghe1, S Staelens, R Van de Walle

  • 1Medical imaging and signal processing (MEDISIP), ELIS, Ghent University, Belgium. Stefaan.Vandenberghe@Philips.com

Nuclear Medicine Communications
|August 13, 2005
PubMed
Summary

A new sorting and compression method significantly reduces listmode data size for 3D PET imaging. This method optimizes storage and speeds up 3D PET reconstructions without information loss.

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Area of Science:

  • Nuclear Medicine
  • Medical Imaging
  • Data Compression

Background:

  • Listmode data storage is increasingly relevant for advanced nuclear medicine imaging like 3D PET.
  • Traditional histogram formats struggle with the large datasets generated by modern imaging techniques.
  • Listmode data compression is crucial due to the significant storage requirements of 3D PET.

Purpose of the Study:

  • To develop and evaluate a sorting and compression method for listmode data.
  • To reduce the storage space required for 3D PET listmode datasets.
  • To improve the efficiency of 3D PET reconstructions using compressed listmode data.

Main Methods:

  • A novel sorting algorithm arranges listmode events into an array of increasing numbers.
  • The sorted data is compressed using the gzip routine, ensuring no information loss.

Related Experiment Videos

  • Positional accuracy in listmode datasets was evaluated for its impact on reconstruction resolution.

    • Main Results:

    • The proposed method significantly reduces listmode dataset size prior to lossless compression.
    • Storage space reduction is observed to be linear with the logarithm of the number of coincidences.
    • 3D PET reconstructions using sorted listmode data demonstrate faster processing due to improved cache behavior.

    Conclusions:

    • The sorting and compression technique effectively reduces listmode data storage requirements.
    • This method enhances the efficiency of 3D PET reconstructions.
    • The technique is applicable to all listmode data, with compression improving as event ratios increase.