Developments in PEPT for process applications

David J. Parker*, A. Sadrmomtaz, X. Fan, A. Ingram

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution


For over 20 years the use of positron-emitting radioactive tracers for engineering studies has been pioneered at Birmingham. The technique of positron emission particle tracking (PEPT) was developed as a variant of the standard medical imaging technique of positron emission tomography (PET), and has proved an extremely powerful tool for studying flow processes inside real laboratory-scale process equipment. Routine studies use a positron camera comprising a pair of digital gamma cameras, which was purchased in 1999. During 2002-4 the old cyclotron previously used for generating the necessary radioactive tracers was replaced by a newer and more powerful cyclotron (moved from Minneapolis) and as a result a wider range of tracer particles can now be produced.

Recently the Positron Imaging Centre acquired an old medical PET scanner, which used rings of small bismuth germanate crystals as the gamma-ray detection elements. This scanner has been rebuilt in a flexible geometry and will be used for PEPT studies. Compared with the present positron camera, it offers the prospect of higher data rates, allowing more accurate tracking at high speed, and also the possibility of making measurements on larger vessels.

Original languageEnglish
Title of host publication4th World Congress in Industrial Process Tomography
PublisherInternational Society for Industrial Process Tomography
Number of pages6
ISBN (Electronic)9780853163206
Publication statusPublished - 1 Jan 2005
Event4th World Congress in Industrial Process Tomography - Aizu, Japan
Duration: 5 Sept 20055 Sept 2005

Publication series

Name4th World Congress in Industrial Process Tomography


Conference4th World Congress in Industrial Process Tomography


  • Particle tracking
  • Radioisotope tracers

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Mechanics
  • Computer Vision and Pattern Recognition
  • Computer Science Applications


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