SPECT ELECTRONIC COLLIMATION RESOLUTION ENHANCEMENT USING CHI-SQUARE MINIMIZATION

An electronic collimation technique is developed which utilizes the ch i-square goodness-of-fit measure to filter scattered gammas incident u pon a medical imaging detector. In this data mining technique, Compton kinematic expressions are used as the chi-square fitting templates fo r measured energy-deposition data involving multiple-interaction scatt er sequences. Fit optimization is conducted using the Davidon variable metric minimization algorithm to simultaneously determine the best-fi t gamma scatter angles and their associated uncertainties, with the un certainty associated with the first scatter angle corresponding to the angular resolution precision for the source. The methodology requires no knowledge of materials and geometry. This pattern recognition appl ication enhances the ability to select those gammas that will provide the best resolution for input to reconstruction software. Illustrative computational results are presented for a conceptual truncated-ellips oid polystyrene position-sensitive fibre head-detector Monte Carlo mod el using a triple Compton scatter gamma sequence assessment for a Tc-9 9m point source. A filtration rate of 94.3% is obtained, resulting in an estimated sensitivity approximately three orders of magnitude great er than a high-resolution mechanically collimated device. The techniqu e improves the nominal single-scatter angular resolution by up to appr oximately 24 per cent as compared with the conventional analytic elect ronic collimation measure.