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

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.