Image reconstruction for positron-emission tomography when anatomical boundaries are known

摘要: Summary form only given, as follows. A method is proposed for improving estimates of radioactivity distributions obtained with PET (positron emission tomography) by utilizing anatomical information derived from MRI (magnetic resonance imaging) or X-ray CT (computered tomography). An algorithm identified computing regularized maximum-likelihood (ML) distributions, subject to the constraint that a region image known boundaries contains an unknown but constant intensity radioactivity. Regularized ML are computed using expectation-maximization algorithm. regularization spatially varying sieve and resolution kernels used prevent artifacts while preserving sharp where appropriate. The evaluated simulation found produce more accurate than filtered backprojection usual variance constrained estimator also studied. >