Fast algorithm for iterative image reconstruction with a small animal positron emission tomograph YAP‐PET (in English)

Abstract

A fast deconvolutive expectation maximization algorithm for iterative image reconstruction was developed for use with a small animal positron emission tomograph YAP‐PET built by the Medical Physics Group at Ferrara University. It has a FOV of 4 cm diam×4 cm axially. In PET modality, the tomograph has a sensitivity of 640 cps/μCi at its center and a spatial resolution of 1.8 mm FWHM. In SPECT, the sensitivity is 2.1 cps/μCi for each detector head, with a spatial resolution of 3.5 mm FWHM. The 3D‐FBP algorithm, usually used for image reconstruction, has a limited angle due to the geometry of the tomograph, which causes a serious loss in sensitivity. We developed an iterative method using the symmetries and the sparse properties of the “probability matrix,” which correlates the emission from each voxel to the detector within a coincidence tube, which we calculated before the reconstruction. We stored only a fraction of matrix elements on disk, thus avoiding on‐line computation, that needs to be performed for the projection and the backprojection steps. This reduces the required storage space by a factor of and the time per iteration from hours to minutes or tens of minutes. A deconvolutive model differentiates the voxels according to their depth in a coincidence tube. This algorithm is used for both PET and SPECT data. It improves the signal‐to‐noise ratio and the spatial resolution. Additionally it allows quantitative data to be available on images in the SPECT mode for cardiac perfusion and uptake studies using 99m‐Tc labeled radiopharmaceuticals.