Bayesian estimator for positron emission tomography imaging using a prior image model with mixed continuity constraints

摘要

A novel image prior with mixed continuity constraints is proposed for the Bayesian positron emission tomography image re- construction of human brains. Assume that a human brain can be partitioned into four tissue classes: gray matter, white matter, cere- bral spinal fluid, and partial volume. And each partical volume image voxel consists of an arbitrary mixture among pure tissues.