Abstract
Abstract
Noise reduction while preserving spatial resolution is one of the most important challenges in the reconstructing of emission tomography images. One of the resolving methods is the Bowsher maximum a-posteriori expectation-maximization reconstruction (MAPEM) algorithm. This method considers a binary selection of the neighbors of each voxel based on the prior anatomical values to use in the regularization function. This method is particularly susceptible to imposing the wrong data into the reconstructed image due to the spatial or functional inconsistencies between the anatomical image and the actual activity distribution. Because of the poor spatial resolution of single-photon emission tomography (SPECT) images and the different nature of emission and anatomical imaging, there is not enough certainty of inconsistency with anatomical images. Therefore, we proposed a new weighted Bowsher method that can overcome this weakness while the image quality indexes, especially the spatial resolution, are almost preserved. In the proposed method, each of the neighbors of a specific voxel takes a constant weight depending on the order of its value and independent of its intensity quantity. The proposed method was evaluated using some different physical phantoms and a patient scan. The results show that the proposed method has superiority in the presence of inconsistency; moreover, the proposed method gives nearly similar results to the regular Bowsher MAPEM in case of consistency. In conclusion, we show that using a suitable constant weighting factor in Bowsher MAPEM, one can operatively reduce the image noise while preserving the image quality parameters where the emission tomography images are either consistent or inconsistent with the prior anatomical map.