Approximate reconstruction of PET data with a self-organizing neural network | IEEE Journals & Magazine | IEEE Xplore

Approximate reconstruction of PET data with a self-organizing neural network


Abstract:

Self-organization was observed using the algorithm of Kohonen with an original "distance" adapted to stimuli resulting from coincident detections of electron-positron ann...Show More

Abstract:

Self-organization was observed using the algorithm of Kohonen with an original "distance" adapted to stimuli resulting from coincident detections of electron-positron annihilation photon pairs. This has led to a method for approximate reconstruction of two-dimensional positron emission tomography (2-D PET) images that is totally independent of the number of detectors. To obtain meaningful information about the distribution of the radioactive tracer, a toroidal architecture must be used for the network.<>
Published in: IEEE Transactions on Neural Networks ( Volume: 6, Issue: 3, May 1995)
Page(s): 783 - 789
Date of Publication: 31 May 1995

ISSN Information:

PubMed ID: 18263366

References

References is not available for this document.