3D position of radiation sources using an automated gamma camera and ML algorithm with energy-dependent response functions

In this work, the 3D position information of a radiation source is determined by a compact gamma ray imaging system. 2D gamma ray images were obtained from different positions by the gamma camera and the third dimension, the distance between the detector and the radiation source, was calculated using triangulation. Additionally, a CCD camera is attached to the top of the gamma camera and provides coincident 2D visual information. The inferred distances from the center of the two measurement points and a radiation source had less than a 5% error within a range of 3m. From the measured distances and camera intrinsic efficiencies /spl epsiv/(/spl theta/,/spl phi/) from MCNP simulations, the activity of the source was normally determined within 80% of the true value depending upon source position. The parallax between the two visual images was corrected using the inferred distance between the detector and the radiation source. The radiation image from gamma camera and the visual image from CCD camera are superimposed into one combined image using a maximum-likelihood (ML) algorithm to make the image alignment more precise. Energy dependent response functions were found to be better than a fixed energy response function for ML image processing.